Simulace.info - User contributions [en]

File:LTG.jpg

2015-02-01T21:38:50Z

Xcesj04:

File:Balancing.jpg

2015-02-01T21:34:51Z

Xcesj04: uploaded a new version of "File:Balancing.jpg"

File:Balancing.jpg

2015-02-01T21:33:47Z

Xcesj04:

File:Reinforcing.jpg

2015-02-01T21:28:24Z

Xcesj04:

File:Jay f.jpg

2015-02-01T20:37:15Z

Xcesj04: uploaded a new version of "File:Jay f.jpg": source: http://history-computer.com/ModernComputer/Electronic/Images/jay_forrester.jpg

File:Jay f.jpg

2015-02-01T20:35:44Z

Xcesj04:

File:Quiz result.png

2015-02-01T20:17:31Z

Xcesj04:

Results

2015-02-01T20:17:06Z

Xcesj04:

[[File:quiz_result.png]]

Results

2015-02-01T20:14:55Z

Xcesj04: Created page with "File:quiz_result.jpg"

[[File:quiz_result.jpg]]

WS 2014/2015

2015-02-01T19:29:48Z

Xcesj04: /* Papers */

Semestral papers from winter term 2014/2015. Please, put here links to the pages with your paper. First you need to have your [[Assignments WS 2014/2015|assignment approved]].

==Simulations==

--[[User:Zhua00|Andriy Zhubryd]] 14:24, 15 January 2015 (CET) [[E-Sim Optimal Equipment Selection]]

--[[User:Xgubk00|Xgubk00]] 12:24, 17 January 2015 (CET) [[Flood evacuation]]

-- [[User:Xzasj00|Xzasj00]] 00:07, 18 January 2015 (CET) [[Formula 1 teams economic situation]]

-- [[User:Qnovm21|Qnovm21]] 10:33, 18 January 2015 (CET) [[Simulation of the surgery staff in a hospital]]

-- [[User:Xzigm03|Xzigm03]] 23:40, 18 January 2015 (CET) [[Poker probabilities and variance simulation]]

-- [[User:Xkraj119|Xkraj119]] 14:41, 24 January 2015 (CET) [[Software Support Lifecycle]]

-- [[User:Xcesj04|Xcesj04]] 23:00, 25 January 2015 (CET) [[Ideal latency between a metro trains]]

-- [[User:Xpalj24|Xpalj24]] 23:00, 25 January 2015 (CET) [[Hearthstone Mulligan]]

==Papers==

--[[User:Xgubk00|Xgubk00]] 12:24, 17 January 2015 (CET) [[Game theory]]

--[[User:Qnovm21|Qnovm21]] 16:40, 21 January 2015 (CET) [[Causal loop diagram]]

--[[User:Xkraj119|Xkraj119]] 10:32, 24 January 2015 (CET) [https://en.wikipedia.org/wiki/Growth_and_underinvestment Growth and Underinvestment Archetype]

--[[User:Xzasj00|Xzasj00]] 18:57, 24 January 2015 (CET) [https://en.wikipedia.org/wiki/Escalation_Archetype Escalation Archetype]

--[[User:Xzigm03|Xzigm03]] 23:11, 25 January 2015 (CET) [[Queueing theory]]

--[[User:Xcesj04|Xcesj04]] 23:50, 1 February 2015 (CET) [[System Dynamics]]

WS 2014/2015

2015-02-01T19:29:13Z

Xcesj04: /* Papers */

WS 2014/2015

2015-02-01T19:28:56Z

Xcesj04: /* Papers */

WS 2014/2015

2015-02-01T19:27:48Z

Xcesj04: /* Papers */

WS 2014/2015

2015-02-01T19:27:26Z

Xcesj04: /* Papers */

Semestral papers from winter term 2014/2015. Please, put here links to the pages with your paper. First you need to have your [[Assignments WS 2014/2015|assignment approved]].

==Simulations==

--[[User:Zhua00|Andriy Zhubryd]] 14:24, 15 January 2015 (CET) [[E-Sim Optimal Equipment Selection]]

--[[User:Xgubk00|Xgubk00]] 12:24, 17 January 2015 (CET) [[Flood evacuation]]

-- [[User:Xzasj00|Xzasj00]] 00:07, 18 January 2015 (CET) [[Formula 1 teams economic situation]]

-- [[User:Qnovm21|Qnovm21]] 10:33, 18 January 2015 (CET) [[Simulation of the surgery staff in a hospital]]

-- [[User:Xzigm03|Xzigm03]] 23:40, 18 January 2015 (CET) [[Poker probabilities and variance simulation]]

-- [[User:Xkraj119|Xkraj119]] 14:41, 24 January 2015 (CET) [[Software Support Lifecycle]]

-- [[User:Xcesj04|Xcesj04]] 23:00, 25 January 2015 (CET) [[Ideal latency between a metro trains]]

-- [[User:Xpalj24|Xpalj24]] 23:00, 25 January 2015 (CET) [[Hearthstone Mulligan]]

==Papers==

--[[User:Xgubk00|Xgubk00]] 12:24, 17 January 2015 (CET) [[Game theory]]

--[[User:Qnovm21|Qnovm21]] 16:40, 21 January 2015 (CET) [[Causal loop diagram]]

--[[User:Xkraj119|Xkraj119]] 10:32, 24 January 2015 (CET) [https://en.wikipedia.org/wiki/Growth_and_underinvestment Growth and Underinvestment Archetype]

--[[User:Xzasj00|Xzasj00]] 18:57, 24 January 2015 (CET) [https://en.wikipedia.org/wiki/Escalation_Archetype Escalation Archetype]

--[[User:Xzigm03|Xzigm03]] 23:11, 25 January 2015 (CET) [[Queueing theory]]

--[[User:Xzigm03|Xzigm03]] 23:50, 1 February 2015 (CET) [[System Dynamics]]

Ideal latency between a metro trains

2015-01-29T17:29:45Z

Xcesj04:

Simulation should represent what latency can be set for passagers transport in the Prague metro (depending on the density of passagers).

= Assignment =
Project Name: Ideal latency between a metro trains
Author: Bc. Jan Cestr
Software used: NetLogo
Class: 4IT496 Simulation of Systems (WS 2014/2015)

= Object =
Finding the minimum and maximum limits (time) for the Prague metro (Line C) which would reveal ideal spacing of each metro trains.
Train should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases).
It should be reckon with the fact that metro station can’t be overfull.

=What is the target of this model?=
Try to get:
1) The biggest value at the transport capacity graph
2) Minimized number of waiting passagers in stations at “passagers at stations” graph
3) Avoid the traffic jam
4) Less people at station (you will see the red flash when is overcrowded)

=Global variables=
===train_capacity===
Capacity of one train.
One graphic character depicts ten real people.

===trains_Delay===
Indicates the spacing between trains

===add_pass_delay===
Speed rate of arrival passagers

===num of stations===
Set the number of stations in model. Model is adapting scale by this value

===rank_xy===
Set the rank of outcoming passagers

==Graphs:==
===transfer capacity===
The graph show the capacity of subway per hour . There is describe that about 1440 tickes is one real hour and graph show capacity of passagers per hour. Wikipedia show that subway metro (C) transport about 26,900 per hour in high-peak – it’s nearly the same amount as in the model.

[[File:transfer_cap.jpg]]

===Passengers at stations===
Number of passagers whose waiting on train. Passagers whose leaves the train are not count in this graph.

[[File:pass.png]]

=How does the simulation work=
Each station has set a parameter stations_min stations_max which indicating the number of people who may come to the station together
(it's the random number from the specified minimum to maximum). So it‘s clear that the final station must be set to 0.
People turn red if the station is overcrowded – in this situation another people cannot come to this station.
Each passenger has set station_id that indicate the station ID which is going to get off.
Outgoing passagers are shown under the platform in the model, after a while they disappear (offcourse - station_id is not set after that).
In the station can not be two trains at one time. The train could delay in station due to large number of incoming and outgoing passager (it‘s added 0.5 tick to waiting for train departures for each one).
If this happens the following trains are waiting in the tunnel for departure from station of previous train.
User can choose attribute value station_ranks (slider rank_xx) for each station. High number represent high probability that passenger exit the train in that station.

Incoming and outgoing passengers at stations

[[File:Pass_num.png]]

Sources: http://geography.upol.cz/soubory/studium/bp/2014-rg/2014_Nezval.pdf

=Model=
I developed a one-way traffic simulation based on real data obtained from the
[http://www.dpp.cz/download-file/8795/annual_report_2013.pdf annual report] and [http://geography.upol.cz/soubory/studium/bp/2014-rg/2014_Nezval.pdf DPP study].
Each station has set ratio on a scale from zero to one, which indicates the probability of outgoing passengers in the station.
The lowest value has station Prosek (0.07), while the I.P. Pavlova has the highest value of (0.79) – as you can see in the chart.
Because it is a one-way simulation the first station (Letňany) has incoming passengers, so the station does not show any ratio.
Station Haje has only outgoing passengers because there is not any next station to go.
There are two time zones in the simulation - the first one is peak, which takes place in time from 7am to 9am and from 4pm to 6pm and second one dedicated to off-peak time.

Default delay between trains is set to 76 ticks.
I recommended you to try and set the biggest rank for the “big“ stations with set minimum and maximum. But as you can see – it still works.

==How to set up typical day?==
When simulation started it could be the best setup long period in the parameter add_pass_delay. I think that you know why - it‘s morning, it means less people there. After that I recommended to you goes to the high-peak gradually. If you don’t do this, some of the station will be overcrowded in high-peak meanwhile the first train goes to the end station.

= Results=
From the information obtained on the Internet, it was found that metro is almost always full at peak, which indicates the validity of this simulation model. There are about 19 metro trains per hour in the simulation, which also corresponds with a reality (in fact, there are 39 trains in peak but this value has half value because of one-way traffic simulation).

===Peak===
An analysis based on simulation, I found that if the train delay between trains is set to less than 76 or more than 81 seconds, trains start to wait in tunnel between stations to departure of the previous train. The value that avoids overcrowding station and trains are effectively filled, moves around xy seconds.
Transport capacity is about 26,900 persons per hour at peak. Simulation has only half value because of one-way traffic.

Ideal setting (76 seconds delay between the trains)
[[File:peak_ideal.png]]
[[File:ideal3.jpg]]

Traffic jam (train waiting in tunnel) when I set up 66 seconds delay between the trains.
[[File:peak.png]]

Traffic jam (train waiting in tunnel) when I set up 86 seconds delay between the trains.
[[File:peak2.png]]

===Off-peak===
Value is reduced occurrence of new passengers (add_pass_delay) on 63 seconds during the off-peak. This was set because of fact, that there are only 12,600 passengers per hour at this time, which is 2,1 times less than at the peak.
Trains are effectively fulffiled when the values are set up to 311 second. Trains are overcrowded if the value is higher than that. Minimum delay between the trains it could be set up to 36 seconds if you choose less than that the trains will be jammed.

Minimum delay between the trains (value is set up to 36)
[[File:of36.png]]

[[File:of36_2.png]]
[[File:of36_3.png]]

=Conslusion=
It seems that ratio which is set up today at peak is ideal. The trains If the company has set another time trains would be jammed. So 'high five' to DPP :)
At off-peak I found ideal latency between metro at value which represents 5 minutes - so it's almost identical to typical working day.

In real life is delay sometimes set up to less time than we analyzed, so it seems that company is not effective, but you know - it’s probably for increased comfort for passengers who don’t want to wait.

Model could be extended in the future - there are some possibilities like as adding depot for some trains (you know - like Kačerov where some trains terminates) or the line from station Háje to station Letňany.
And of course due to option to change number of station and a lot of variables you could build your own metro.

=Code=
[[File:Metro.nlogo]]

File:Metro.nlogo

2015-01-25T22:59:36Z

Xcesj04:

File:Ideal3.jpg

2015-01-25T22:57:16Z

Xcesj04:

Ideal latency between a metro trains

2015-01-25T22:56:35Z

Xcesj04: /* Peak */

Simulation should represent what latency can be set for passagers transport in the Prague metro (depending on the density of passagers).

= Assignment =
Project Name: Ideal latency between a metro trains
Author: Bc. Jan Cestr
Software used: NetLogo
Class: 4IT496 Simulation of Systems (WS 2014/2015)

= Object =
Finding the minimum and maximum limits (time) for the Prague metro (Line C) which would reveal ideal spacing of each metro trains.
Train should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases).
It should be reckon with the fact that metro station can’t be overfull.

=What is the target of this model?=
Try to get:
1) The biggest value at the transport capacity graph
2) Minimized number of waiting passagers in stations at “passagers at stations” graph
3) Avoid the traffic jam
4) Less people at station (you will see the red flash when is overcrowded)

=Global variables=
===train_capacity===
Capacity of one train.
One graphic character depicts ten real people.

===trains_Delay===
Indicates the spacing between trains

===add_pass_delay===
Speed rate of arrival passagers

===num of stations===
Set the number of stations in model. Model is adapting scale by this value

===rank_xy===
Set the rank of outcoming passagers

==Graphs:==
===transfer capacity===
The graph show the capacity of subway per hour . There is describe that about 1440 tickes is one real hour and graph show capacity of passagers per hour. Wikipedia show that subway metro (C) transport about 26,900 per hour in high-peak – it’s nearly the same amount as in the model.

[[File:transfer_cap.jpg]]

===Passengers at stations===
Number of passagers whose waiting on train. Passagers whose leaves the train are not count in this graph.

[[File:pass.png]]

=How does the simulation work=
Each station has set a parameter stations_min stations_max which indicating the number of people who may come to the station together
(it's the random number from the specified minimum to maximum). So it‘s clear that the final station must be set to 0.
People turn red if the station is overcrowded – in this situation another people cannot come to this station.
Each passenger has set station_id that indicate the station ID which is going to get off.
Outgoing passagers are shown under the platform in the model, after a while they disappear (offcourse - station_id is not set after that).
In the station can not be two trains at one time. The train could delay in station due to large number of incoming and outgoing passager (it‘s added 0.5 tick to waiting for train departures for each one).
If this happens the following trains are waiting in the tunnel for departure from station of previous train.
User can choose attribute value station_ranks (slider rank_xx) for each station. High number represent high probability that passenger exit the train in that station.

Incoming and outgoing passengers at stations

[[File:Pass_num.png]]

Sources: http://geography.upol.cz/soubory/studium/bp/2014-rg/2014_Nezval.pdf

=Model=
I developed a one-way traffic simulation based on real data obtained from the annual report and DPP study xyz.
Each station has set ratio on a scale from zero to one, which indicates the probability of outgoing passengers in the station.
The lowest value has station Prosek (0.07), while the I.P. Pavlova has the highest value of (0.79) – as you can see in the chart.
Because it is a one-way simulation the first station (Letňany) has incoming passengers, so the station does not show any ratio.
Station Haje has only outgoing passengers because there is not any next station to go.
There are two time zones in the simulation - the first one is peak, which takes place in time from 7am to 9am and from 5pm to 9pm and second one dedicated to off-peak time.

Default delay between trains is set to 76 ticks.
I recommended you to try and set the biggest rank for the “big“ stations with set minimum and maximum. But as you can see – it still works.

==How to set up typical day?==
When simulation started it could be the best setup long period in the parameter add_pass_delay. I think that you know why - it‘s morning, it means less people there. After that I recommended to you goes to the high-peak gradually. If you don’t do this, some of the station will be overcrowded in high-peak meanwhile the first train goes to the end station.

= Results=
From the information obtained on the Internet, it was found that metro is almost always full at peak, which indicates the validity of this simulation model. There are about 19 metro trains per hour in the simulation, which also corresponds with a reality (in fact, there are 39 trains in peak but this value has half value because of one-way traffic simulation).

===Peak===
An analysis based on simulation, I found that if the train delay between trains is set to less than 76 or more than 81 seconds, trains start to wait in tunnel between stations to departure of the previous train. The value that avoids overcrowding station and trains are effectively filled, moves around xy seconds.
Transport capacity is about 26,900 persons per hour at peak. Simulation has only half value because of one-way traffic.

Ideal setting (76 seconds delay between the trains)
[[File:peak_ideal.png]]
[[File:ideal3.jpg]]

Traffic jam (train waiting in tunnel) when I set up 66 seconds delay between the trains.
[[File:peak.png]]

Traffic jam (train waiting in tunnel) when I set up 86 seconds delay between the trains.
[[File:peak2.png]]

===Off-peak===
Value is reduced occurrence of new passengers (add_pass_delay) on 63 seconds during the off-peak. This was set because of fact, that there are only 12,600 passengers per hour at this time, which is 2,1 times less than at the peak.
Trains are effectively fulffiled when the values are set up to 311 second. Trains are overcrowded if the value is higher than that. Minimum delay between the trains it could be set up to 36 seconds if you choose less than that the trains will be jammed.

Minimum delay between the trains (value is set up to 36)
[[File:of36.png]]

[[File:of36_2.png]]
[[File:of36_3.png]]

=Conslusion=
It seems that ratio which is set up today at peak is ideal. The trains If the company has set another time trains would be jammed. So 'high five' to DPP :)
At off-peak I found ideal latency between metro at value which represents 5 minutes - so it's almost identical to typical working day.

In real life is delay sometimes set up to less time than we analyzed, so it seems that company is not effective, but you know - it’s probably for increased comfort for passengers who don’t want to wait.

Model could be extended in the future - there are some possibilities like as adding depot for some trains (you know - like Kačerov where some trains terminates) or the line from station Háje to station Letňany.
And of course due to option to change number of station and a lot of variables you could build your own metro.

File:Peak ideal.png

2015-01-25T22:55:56Z

Xcesj04: uploaded a new version of "File:Peak ideal.png"

File:Peak ideal.png

2015-01-25T22:54:44Z

Xcesj04:

Ideal latency between a metro trains

2015-01-25T22:53:01Z

Xcesj04: /* How does the simulation work */

Simulation should represent what latency can be set for passagers transport in the Prague metro (depending on the density of passagers).

= Assignment =
Project Name: Ideal latency between a metro trains
Author: Bc. Jan Cestr
Software used: NetLogo
Class: 4IT496 Simulation of Systems (WS 2014/2015)

= Object =
Finding the minimum and maximum limits (time) for the Prague metro (Line C) which would reveal ideal spacing of each metro trains.
Train should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases).
It should be reckon with the fact that metro station can’t be overfull.

=What is the target of this model?=
Try to get:
1) The biggest value at the transport capacity graph
2) Minimized number of waiting passagers in stations at “passagers at stations” graph
3) Avoid the traffic jam
4) Less people at station (you will see the red flash when is overcrowded)

=Global variables=
===train_capacity===
Capacity of one train.
One graphic character depicts ten real people.

===trains_Delay===
Indicates the spacing between trains

===add_pass_delay===
Speed rate of arrival passagers

===num of stations===
Set the number of stations in model. Model is adapting scale by this value

===rank_xy===
Set the rank of outcoming passagers

==Graphs:==
===transfer capacity===
The graph show the capacity of subway per hour . There is describe that about 1440 tickes is one real hour and graph show capacity of passagers per hour. Wikipedia show that subway metro (C) transport about 26,900 per hour in high-peak – it’s nearly the same amount as in the model.

[[File:transfer_cap.jpg]]

===Passengers at stations===
Number of passagers whose waiting on train. Passagers whose leaves the train are not count in this graph.

[[File:pass.png]]

=How does the simulation work=
Each station has set a parameter stations_min stations_max which indicating the number of people who may come to the station together
(it's the random number from the specified minimum to maximum). So it‘s clear that the final station must be set to 0.
People turn red if the station is overcrowded – in this situation another people cannot come to this station.
Each passenger has set station_id that indicate the station ID which is going to get off.
Outgoing passagers are shown under the platform in the model, after a while they disappear (offcourse - station_id is not set after that).
In the station can not be two trains at one time. The train could delay in station due to large number of incoming and outgoing passager (it‘s added 0.5 tick to waiting for train departures for each one).
If this happens the following trains are waiting in the tunnel for departure from station of previous train.
User can choose attribute value station_ranks (slider rank_xx) for each station. High number represent high probability that passenger exit the train in that station.

Incoming and outgoing passengers at stations

[[File:Pass_num.png]]

Sources: http://geography.upol.cz/soubory/studium/bp/2014-rg/2014_Nezval.pdf

=Model=
I developed a one-way traffic simulation based on real data obtained from the annual report and DPP study xyz.
Each station has set ratio on a scale from zero to one, which indicates the probability of outgoing passengers in the station.
The lowest value has station Prosek (0.07), while the I.P. Pavlova has the highest value of (0.79) – as you can see in the chart.
Because it is a one-way simulation the first station (Letňany) has incoming passengers, so the station does not show any ratio.
Station Haje has only outgoing passengers because there is not any next station to go.
There are two time zones in the simulation - the first one is peak, which takes place in time from 7am to 9am and from 5pm to 9pm and second one dedicated to off-peak time.

Default delay between trains is set to 76 ticks.
I recommended you to try and set the biggest rank for the “big“ stations with set minimum and maximum. But as you can see – it still works.

==How to set up typical day?==
When simulation started it could be the best setup long period in the parameter add_pass_delay. I think that you know why - it‘s morning, it means less people there. After that I recommended to you goes to the high-peak gradually. If you don’t do this, some of the station will be overcrowded in high-peak meanwhile the first train goes to the end station.

= Results=
From the information obtained on the Internet, it was found that metro is almost always full at peak, which indicates the validity of this simulation model. There are about 19 metro trains per hour in the simulation, which also corresponds with a reality (in fact, there are 39 trains in peak but this value has half value because of one-way traffic simulation).

===Peak===
An analysis based on simulation, I found that if the train delay between trains is set to less than 76 or more than 81 seconds, trains start to wait in tunnel between stations to departure of the previous train. The value that avoids overcrowding station and trains are effectively filled, moves around xy seconds.
Transport capacity is about 26,900 persons per hour at peak. Simulation has only half value because of one-way traffic.

Ideal setting (76 seconds delay between the trains)
[[File:peak_ideal.png]]

Traffic jam (train waiting in tunnel) when I set up 66 seconds delay between the trains.
[[File:peak.png]]

Traffic jam (train waiting in tunnel) when I set up 86 seconds delay between the trains.
[[File:peak2.png]]

===Off-peak===
Value is reduced occurrence of new passengers (add_pass_delay) on 63 seconds during the off-peak. This was set because of fact, that there are only 12,600 passengers per hour at this time, which is 2,1 times less than at the peak.
Trains are effectively fulffiled when the values are set up to 311 second. Trains are overcrowded if the value is higher than that. Minimum delay between the trains it could be set up to 36 seconds if you choose less than that the trains will be jammed.

Minimum delay between the trains (value is set up to 36)
[[File:of36.png]]

[[File:of36_2.png]]
[[File:of36_3.png]]

=Conslusion=
It seems that ratio which is set up today at peak is ideal. The trains If the company has set another time trains would be jammed. So 'high five' to DPP :)
At off-peak I found ideal latency between metro at value which represents 5 minutes - so it's almost identical to typical working day.

In real life is delay sometimes set up to less time than we analyzed, so it seems that company is not effective, but you know - it’s probably for increased comfort for passengers who don’t want to wait.

Model could be extended in the future - there are some possibilities like as adding depot for some trains (you know - like Kačerov where some trains terminates) or the line from station Háje to station Letňany.
And of course due to option to change number of station and a lot of variables you could build your own metro.

File:Pass num.png

2015-01-25T22:49:30Z

Xcesj04:

Ideal latency between a metro trains

2015-01-25T22:43:56Z

Xcesj04: /* Off-peak */

Simulation should represent what latency can be set for passagers transport in the Prague metro (depending on the density of passagers).

= Assignment =
Project Name: Ideal latency between a metro trains
Author: Bc. Jan Cestr
Software used: NetLogo
Class: 4IT496 Simulation of Systems (WS 2014/2015)

= Object =
Finding the minimum and maximum limits (time) for the Prague metro (Line C) which would reveal ideal spacing of each metro trains.
Train should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases).
It should be reckon with the fact that metro station can’t be overfull.

=What is the target of this model?=
Try to get:
1) The biggest value at the transport capacity graph
2) Minimized number of waiting passagers in stations at “passagers at stations” graph
3) Avoid the traffic jam
4) Less people at station (you will see the red flash when is overcrowded)

=Global variables=
===train_capacity===
Capacity of one train.
One graphic character depicts ten real people.

===trains_Delay===
Indicates the spacing between trains

===add_pass_delay===
Speed rate of arrival passagers

===num of stations===
Set the number of stations in model. Model is adapting scale by this value

===rank_xy===
Set the rank of outcoming passagers

==Graphs:==
===transfer capacity===
The graph show the capacity of subway per hour . There is describe that about 1440 tickes is one real hour and graph show capacity of passagers per hour. Wikipedia show that subway metro (C) transport about 26,900 per hour in high-peak – it’s nearly the same amount as in the model.

[[File:transfer_cap.jpg]]

===Passengers at stations===
Number of passagers whose waiting on train. Passagers whose leaves the train are not count in this graph.

[[File:pass.png]]

=How does the simulation work=
Each station has set a parameter stations_min stations_max which indicating the number of people who may come to the station together
(it's the random number from the specified minimum to maximum). So it‘s clear that the final station must be set to 0.
People turn red if the station is overcrowded – in this situation another people cannot come to this station.
Each passenger has set station_id that indicate the station ID which is going to get off.
Outgoing passagers are shown under the platform in the model, after a while they disappear (offcourse - station_id is not set after that).
In the station can not be two trains at one time. The train could delay in station due to large number of incoming and outgoing passager (it‘s added 0.5 tick to waiting for train departures for each one).
If this happens the following trains are waiting in the tunnel for departure from station of previous train.
User can choose attribute value station_ranks (slider rank_xx) for each station. High number represent high probability that passenger exit the train in that station.

=Model=
I developed a one-way traffic simulation based on real data obtained from the annual report and DPP study xyz.
Each station has set ratio on a scale from zero to one, which indicates the probability of outgoing passengers in the station.
The lowest value has station Prosek (0.07), while the I.P. Pavlova has the highest value of (0.79) – as you can see in the chart.
Because it is a one-way simulation the first station (Letňany) has incoming passengers, so the station does not show any ratio.
Station Haje has only outgoing passengers because there is not any next station to go.
There are two time zones in the simulation - the first one is peak, which takes place in time from 7am to 9am and from 5pm to 9pm and second one dedicated to off-peak time.

Default delay between trains is set to 76 ticks.
I recommended you to try and set the biggest rank for the “big“ stations with set minimum and maximum. But as you can see – it still works.

==How to set up typical day?==
When simulation started it could be the best setup long period in the parameter add_pass_delay. I think that you know why - it‘s morning, it means less people there. After that I recommended to you goes to the high-peak gradually. If you don’t do this, some of the station will be overcrowded in high-peak meanwhile the first train goes to the end station.

= Results=
From the information obtained on the Internet, it was found that metro is almost always full at peak, which indicates the validity of this simulation model. There are about 19 metro trains per hour in the simulation, which also corresponds with a reality (in fact, there are 39 trains in peak but this value has half value because of one-way traffic simulation).

===Peak===
An analysis based on simulation, I found that if the train delay between trains is set to less than 76 or more than 81 seconds, trains start to wait in tunnel between stations to departure of the previous train. The value that avoids overcrowding station and trains are effectively filled, moves around xy seconds.
Transport capacity is about 26,900 persons per hour at peak. Simulation has only half value because of one-way traffic.

Ideal setting (76 seconds delay between the trains)
[[File:peak_ideal.png]]

Traffic jam (train waiting in tunnel) when I set up 66 seconds delay between the trains.
[[File:peak.png]]

Traffic jam (train waiting in tunnel) when I set up 86 seconds delay between the trains.
[[File:peak2.png]]

===Off-peak===
Value is reduced occurrence of new passengers (add_pass_delay) on 63 seconds during the off-peak. This was set because of fact, that there are only 12,600 passengers per hour at this time, which is 2,1 times less than at the peak.
Trains are effectively fulffiled when the values are set up to 311 second. Trains are overcrowded if the value is higher than that. Minimum delay between the trains it could be set up to 36 seconds if you choose less than that the trains will be jammed.

Minimum delay between the trains (value is set up to 36)
[[File:of36.png]]

[[File:of36_2.png]]
[[File:of36_3.png]]

=Conslusion=
It seems that ratio which is set up today at peak is ideal. The trains If the company has set another time trains would be jammed. So 'high five' to DPP :)
At off-peak I found ideal latency between metro at value which represents 5 minutes - so it's almost identical to typical working day.

In real life is delay sometimes set up to less time than we analyzed, so it seems that company is not effective, but you know - it’s probably for increased comfort for passengers who don’t want to wait.

Model could be extended in the future - there are some possibilities like as adding depot for some trains (you know - like Kačerov where some trains terminates) or the line from station Háje to station Letňany.
And of course due to option to change number of station and a lot of variables you could build your own metro.

Ideal latency between a metro trains

2015-01-25T22:42:18Z

Xcesj04: /* Off-peak */

Simulation should represent what latency can be set for passagers transport in the Prague metro (depending on the density of passagers).

= Assignment =
Project Name: Ideal latency between a metro trains
Author: Bc. Jan Cestr
Software used: NetLogo
Class: 4IT496 Simulation of Systems (WS 2014/2015)

= Object =
Finding the minimum and maximum limits (time) for the Prague metro (Line C) which would reveal ideal spacing of each metro trains.
Train should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases).
It should be reckon with the fact that metro station can’t be overfull.

=What is the target of this model?=
Try to get:
1) The biggest value at the transport capacity graph
2) Minimized number of waiting passagers in stations at “passagers at stations” graph
3) Avoid the traffic jam
4) Less people at station (you will see the red flash when is overcrowded)

=Global variables=
===train_capacity===
Capacity of one train.
One graphic character depicts ten real people.

===trains_Delay===
Indicates the spacing between trains

===add_pass_delay===
Speed rate of arrival passagers

===num of stations===
Set the number of stations in model. Model is adapting scale by this value

===rank_xy===
Set the rank of outcoming passagers

==Graphs:==
===transfer capacity===
The graph show the capacity of subway per hour . There is describe that about 1440 tickes is one real hour and graph show capacity of passagers per hour. Wikipedia show that subway metro (C) transport about 26,900 per hour in high-peak – it’s nearly the same amount as in the model.

[[File:transfer_cap.jpg]]

===Passengers at stations===
Number of passagers whose waiting on train. Passagers whose leaves the train are not count in this graph.

[[File:pass.png]]

=How does the simulation work=
Each station has set a parameter stations_min stations_max which indicating the number of people who may come to the station together
(it's the random number from the specified minimum to maximum). So it‘s clear that the final station must be set to 0.
People turn red if the station is overcrowded – in this situation another people cannot come to this station.
Each passenger has set station_id that indicate the station ID which is going to get off.
Outgoing passagers are shown under the platform in the model, after a while they disappear (offcourse - station_id is not set after that).
In the station can not be two trains at one time. The train could delay in station due to large number of incoming and outgoing passager (it‘s added 0.5 tick to waiting for train departures for each one).
If this happens the following trains are waiting in the tunnel for departure from station of previous train.
User can choose attribute value station_ranks (slider rank_xx) for each station. High number represent high probability that passenger exit the train in that station.

=Model=
I developed a one-way traffic simulation based on real data obtained from the annual report and DPP study xyz.
Each station has set ratio on a scale from zero to one, which indicates the probability of outgoing passengers in the station.
The lowest value has station Prosek (0.07), while the I.P. Pavlova has the highest value of (0.79) – as you can see in the chart.
Because it is a one-way simulation the first station (Letňany) has incoming passengers, so the station does not show any ratio.
Station Haje has only outgoing passengers because there is not any next station to go.
There are two time zones in the simulation - the first one is peak, which takes place in time from 7am to 9am and from 5pm to 9pm and second one dedicated to off-peak time.

Default delay between trains is set to 76 ticks.
I recommended you to try and set the biggest rank for the “big“ stations with set minimum and maximum. But as you can see – it still works.

==How to set up typical day?==
When simulation started it could be the best setup long period in the parameter add_pass_delay. I think that you know why - it‘s morning, it means less people there. After that I recommended to you goes to the high-peak gradually. If you don’t do this, some of the station will be overcrowded in high-peak meanwhile the first train goes to the end station.

= Results=
From the information obtained on the Internet, it was found that metro is almost always full at peak, which indicates the validity of this simulation model. There are about 19 metro trains per hour in the simulation, which also corresponds with a reality (in fact, there are 39 trains in peak but this value has half value because of one-way traffic simulation).

===Peak===
An analysis based on simulation, I found that if the train delay between trains is set to less than 76 or more than 81 seconds, trains start to wait in tunnel between stations to departure of the previous train. The value that avoids overcrowding station and trains are effectively filled, moves around xy seconds.
Transport capacity is about 26,900 persons per hour at peak. Simulation has only half value because of one-way traffic.

Ideal setting (76 seconds delay between the trains)
[[File:peak_ideal.png]]

Traffic jam (train waiting in tunnel) when I set up 66 seconds delay between the trains.
[[File:peak.png]]

Traffic jam (train waiting in tunnel) when I set up 86 seconds delay between the trains.
[[File:peak2.png]]

===Off-peak===
Value is reduced occurrence of new passengers (add_pass_delay) on 63 seconds during the off-peak. This was set because of fact, that there are only 12,600 passengers per hour at this time, which is 2,1 times less than at the peak.
Trains are effectively fulffiled when the values are set up to 311 second. Trains are overcrowded if the value is higher than that.

Minimum delay between the trains (value is set up to 36)
[[File:of36.png]]

[[File:of36_2.png]]
[[File:of36_3.png]]

=Conslusion=
It seems that ratio which is set up today at peak is ideal. The trains If the company has set another time trains would be jammed. So 'high five' to DPP :)
At off-peak I found ideal latency between metro at value which represents 5 minutes - so it's almost identical to typical working day.

In real life is delay sometimes set up to less time than we analyzed, so it seems that company is not effective, but you know - it’s probably for increased comfort for passengers who don’t want to wait.

Model could be extended in the future - there are some possibilities like as adding depot for some trains (you know - like Kačerov where some trains terminates) or the line from station Háje to station Letňany.
And of course due to option to change number of station and a lot of variables you could build your own metro.

File:Of36 3.png

2015-01-25T22:42:03Z

Xcesj04:

File:Of36 2.png

2015-01-25T22:41:55Z

Xcesj04:

File:Of36.png

2015-01-25T22:41:45Z

Xcesj04:

Ideal latency between a metro trains

2015-01-25T22:37:42Z

Xcesj04: /* Peak */

Simulation should represent what latency can be set for passagers transport in the Prague metro (depending on the density of passagers).

= Assignment =
Project Name: Ideal latency between a metro trains
Author: Bc. Jan Cestr
Software used: NetLogo
Class: 4IT496 Simulation of Systems (WS 2014/2015)

= Object =
Finding the minimum and maximum limits (time) for the Prague metro (Line C) which would reveal ideal spacing of each metro trains.
Train should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases).
It should be reckon with the fact that metro station can’t be overfull.

=What is the target of this model?=
Try to get:
1) The biggest value at the transport capacity graph
2) Minimized number of waiting passagers in stations at “passagers at stations” graph
3) Avoid the traffic jam
4) Less people at station (you will see the red flash when is overcrowded)

=Global variables=
===train_capacity===
Capacity of one train.
One graphic character depicts ten real people.

===trains_Delay===
Indicates the spacing between trains

===add_pass_delay===
Speed rate of arrival passagers

===num of stations===
Set the number of stations in model. Model is adapting scale by this value

===rank_xy===
Set the rank of outcoming passagers

==Graphs:==
===transfer capacity===
The graph show the capacity of subway per hour . There is describe that about 1440 tickes is one real hour and graph show capacity of passagers per hour. Wikipedia show that subway metro (C) transport about 26,900 per hour in high-peak – it’s nearly the same amount as in the model.

[[File:transfer_cap.jpg]]

===Passengers at stations===
Number of passagers whose waiting on train. Passagers whose leaves the train are not count in this graph.

[[File:pass.png]]

=How does the simulation work=
Each station has set a parameter stations_min stations_max which indicating the number of people who may come to the station together
(it's the random number from the specified minimum to maximum). So it‘s clear that the final station must be set to 0.
People turn red if the station is overcrowded – in this situation another people cannot come to this station.
Each passenger has set station_id that indicate the station ID which is going to get off.
Outgoing passagers are shown under the platform in the model, after a while they disappear (offcourse - station_id is not set after that).
In the station can not be two trains at one time. The train could delay in station due to large number of incoming and outgoing passager (it‘s added 0.5 tick to waiting for train departures for each one).
If this happens the following trains are waiting in the tunnel for departure from station of previous train.
User can choose attribute value station_ranks (slider rank_xx) for each station. High number represent high probability that passenger exit the train in that station.

=Model=
I developed a one-way traffic simulation based on real data obtained from the annual report and DPP study xyz.
Each station has set ratio on a scale from zero to one, which indicates the probability of outgoing passengers in the station.
The lowest value has station Prosek (0.07), while the I.P. Pavlova has the highest value of (0.79) – as you can see in the chart.
Because it is a one-way simulation the first station (Letňany) has incoming passengers, so the station does not show any ratio.
Station Haje has only outgoing passengers because there is not any next station to go.
There are two time zones in the simulation - the first one is peak, which takes place in time from 7am to 9am and from 5pm to 9pm and second one dedicated to off-peak time.

Default delay between trains is set to 76 ticks.
I recommended you to try and set the biggest rank for the “big“ stations with set minimum and maximum. But as you can see – it still works.

==How to set up typical day?==
When simulation started it could be the best setup long period in the parameter add_pass_delay. I think that you know why - it‘s morning, it means less people there. After that I recommended to you goes to the high-peak gradually. If you don’t do this, some of the station will be overcrowded in high-peak meanwhile the first train goes to the end station.

= Results=
From the information obtained on the Internet, it was found that metro is almost always full at peak, which indicates the validity of this simulation model. There are about 19 metro trains per hour in the simulation, which also corresponds with a reality (in fact, there are 39 trains in peak but this value has half value because of one-way traffic simulation).

===Peak===
An analysis based on simulation, I found that if the train delay between trains is set to less than 76 or more than 81 seconds, trains start to wait in tunnel between stations to departure of the previous train. The value that avoids overcrowding station and trains are effectively filled, moves around xy seconds.
Transport capacity is about 26,900 persons per hour at peak. Simulation has only half value because of one-way traffic.

Ideal setting (76 seconds delay between the trains)
[[File:peak_ideal.png]]

Traffic jam (train waiting in tunnel) when I set up 66 seconds delay between the trains.
[[File:peak.png]]

Traffic jam (train waiting in tunnel) when I set up 86 seconds delay between the trains.
[[File:peak2.png]]

===Off-peak===
Value is reduced occurrence of new passengers (add_pass_delay) on 63 seconds during the off-peak. This was set because of fact, that there are only 12,600 passengers per hour at this time, which is 2,1 times less than at the peak.
Trains are effectively fulffiled when the values are set up to 311 second. Trains are overcrowded if the value is higher than that.

=Conslusion=
It seems that ratio which is set up today at peak is ideal. The trains If the company has set another time trains would be jammed. So 'high five' to DPP :)
At off-peak I found ideal latency between metro at value which represents 5 minutes - so it's almost identical to typical working day.

In real life is delay sometimes set up to less time than we analyzed, so it seems that company is not effective, but you know - it’s probably for increased comfort for passengers who don’t want to wait.

Model could be extended in the future - there are some possibilities like as adding depot for some trains (you know - like Kačerov where some trains terminates) or the line from station Háje to station Letňany.
And of course due to option to change number of station and a lot of variables you could build your own metro.

Ideal latency between a metro trains

2015-01-25T22:29:31Z

Xcesj04: /* Peak */

Simulation should represent what latency can be set for passagers transport in the Prague metro (depending on the density of passagers).

= Assignment =
Project Name: Ideal latency between a metro trains
Author: Bc. Jan Cestr
Software used: NetLogo
Class: 4IT496 Simulation of Systems (WS 2014/2015)

= Object =
Finding the minimum and maximum limits (time) for the Prague metro (Line C) which would reveal ideal spacing of each metro trains.
Train should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases).
It should be reckon with the fact that metro station can’t be overfull.

=What is the target of this model?=
Try to get:
1) The biggest value at the transport capacity graph
2) Minimized number of waiting passagers in stations at “passagers at stations” graph
3) Avoid the traffic jam
4) Less people at station (you will see the red flash when is overcrowded)

=Global variables=
===train_capacity===
Capacity of one train.
One graphic character depicts ten real people.

===trains_Delay===
Indicates the spacing between trains

===add_pass_delay===
Speed rate of arrival passagers

===num of stations===
Set the number of stations in model. Model is adapting scale by this value

===rank_xy===
Set the rank of outcoming passagers

==Graphs:==
===transfer capacity===
The graph show the capacity of subway per hour . There is describe that about 1440 tickes is one real hour and graph show capacity of passagers per hour. Wikipedia show that subway metro (C) transport about 26,900 per hour in high-peak – it’s nearly the same amount as in the model.

[[File:transfer_cap.jpg]]

===Passengers at stations===
Number of passagers whose waiting on train. Passagers whose leaves the train are not count in this graph.

[[File:pass.png]]

=How does the simulation work=
Each station has set a parameter stations_min stations_max which indicating the number of people who may come to the station together
(it's the random number from the specified minimum to maximum). So it‘s clear that the final station must be set to 0.
People turn red if the station is overcrowded – in this situation another people cannot come to this station.
Each passenger has set station_id that indicate the station ID which is going to get off.
Outgoing passagers are shown under the platform in the model, after a while they disappear (offcourse - station_id is not set after that).
In the station can not be two trains at one time. The train could delay in station due to large number of incoming and outgoing passager (it‘s added 0.5 tick to waiting for train departures for each one).
If this happens the following trains are waiting in the tunnel for departure from station of previous train.
User can choose attribute value station_ranks (slider rank_xx) for each station. High number represent high probability that passenger exit the train in that station.

=Model=
I developed a one-way traffic simulation based on real data obtained from the annual report and DPP study xyz.
Each station has set ratio on a scale from zero to one, which indicates the probability of outgoing passengers in the station.
The lowest value has station Prosek (0.07), while the I.P. Pavlova has the highest value of (0.79) – as you can see in the chart.
Because it is a one-way simulation the first station (Letňany) has incoming passengers, so the station does not show any ratio.
Station Haje has only outgoing passengers because there is not any next station to go.
There are two time zones in the simulation - the first one is peak, which takes place in time from 7am to 9am and from 5pm to 9pm and second one dedicated to off-peak time.

Default delay between trains is set to 76 ticks.
I recommended you to try and set the biggest rank for the “big“ stations with set minimum and maximum. But as you can see – it still works.

==How to set up typical day?==
When simulation started it could be the best setup long period in the parameter add_pass_delay. I think that you know why - it‘s morning, it means less people there. After that I recommended to you goes to the high-peak gradually. If you don’t do this, some of the station will be overcrowded in high-peak meanwhile the first train goes to the end station.

= Results=
From the information obtained on the Internet, it was found that metro is almost always full at peak, which indicates the validity of this simulation model. There are about 19 metro trains per hour in the simulation, which also corresponds with a reality (in fact, there are 39 trains in peak but this value has half value because of one-way traffic simulation).

===Peak===
An analysis based on simulation, I found that if the train delay between trains is set to less than 76 or more than 81 seconds, trains start to wait in tunnel between stations to departure of the previous train. The value that avoids overcrowding station and trains are effectively filled, moves around xy seconds.
Transport capacity is about 26,900 persons per hour at peak. Simulation has only half value because of one-way traffic.

Traffic jam (train waiting in tunnel) when I set up 66 seconds delay between the trains.
[[File:peak.png]]

Traffic jam (train waiting in tunnel) when I set up 86 seconds delay between the trains.
[[File:peak2.png]]

===Off-peak===
Value is reduced occurrence of new passengers (add_pass_delay) on 63 seconds during the off-peak. This was set because of fact, that there are only 12,600 passengers per hour at this time, which is 2,1 times less than at the peak.
Trains are effectively fulffiled when the values are set up to 311 second. Trains are overcrowded if the value is higher than that.

=Conslusion=
It seems that ratio which is set up today at peak is ideal. The trains If the company has set another time trains would be jammed. So 'high five' to DPP :)
At off-peak I found ideal latency between metro at value which represents 5 minutes - so it's almost identical to typical working day.

In real life is delay sometimes set up to less time than we analyzed, so it seems that company is not effective, but you know - it’s probably for increased comfort for passengers who don’t want to wait.

Model could be extended in the future - there are some possibilities like as adding depot for some trains (you know - like Kačerov where some trains terminates) or the line from station Háje to station Letňany.
And of course due to option to change number of station and a lot of variables you could build your own metro.

File:Peak2.png

2015-01-25T22:28:02Z

Xcesj04: Traffic jam at peak (86s)

Traffic jam at peak (86s)

File:Peak.png

2015-01-25T22:26:55Z

Xcesj04: Traffic jam at peak (66s)

Traffic jam at peak (66s)

Ideal latency between a metro trains

2015-01-25T22:25:46Z

Xcesj04: /* What is the target of this model? */

Simulation should represent what latency can be set for passagers transport in the Prague metro (depending on the density of passagers).

= Assignment =
Project Name: Ideal latency between a metro trains
Author: Bc. Jan Cestr
Software used: NetLogo
Class: 4IT496 Simulation of Systems (WS 2014/2015)

= Object =
Finding the minimum and maximum limits (time) for the Prague metro (Line C) which would reveal ideal spacing of each metro trains.
Train should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases).
It should be reckon with the fact that metro station can’t be overfull.

=What is the target of this model?=
Try to get:
1) The biggest value at the transport capacity graph
2) Minimized number of waiting passagers in stations at “passagers at stations” graph
3) Avoid the traffic jam
4) Less people at station (you will see the red flash when is overcrowded)

=Global variables=
===train_capacity===
Capacity of one train.
One graphic character depicts ten real people.

===trains_Delay===
Indicates the spacing between trains

===add_pass_delay===
Speed rate of arrival passagers

===num of stations===
Set the number of stations in model. Model is adapting scale by this value

===rank_xy===
Set the rank of outcoming passagers

==Graphs:==
===transfer capacity===
The graph show the capacity of subway per hour . There is describe that about 1440 tickes is one real hour and graph show capacity of passagers per hour. Wikipedia show that subway metro (C) transport about 26,900 per hour in high-peak – it’s nearly the same amount as in the model.

[[File:transfer_cap.jpg]]

===Passengers at stations===
Number of passagers whose waiting on train. Passagers whose leaves the train are not count in this graph.

[[File:pass.png]]

=How does the simulation work=
Each station has set a parameter stations_min stations_max which indicating the number of people who may come to the station together
(it's the random number from the specified minimum to maximum). So it‘s clear that the final station must be set to 0.
People turn red if the station is overcrowded – in this situation another people cannot come to this station.
Each passenger has set station_id that indicate the station ID which is going to get off.
Outgoing passagers are shown under the platform in the model, after a while they disappear (offcourse - station_id is not set after that).
In the station can not be two trains at one time. The train could delay in station due to large number of incoming and outgoing passager (it‘s added 0.5 tick to waiting for train departures for each one).
If this happens the following trains are waiting in the tunnel for departure from station of previous train.
User can choose attribute value station_ranks (slider rank_xx) for each station. High number represent high probability that passenger exit the train in that station.

=Model=
I developed a one-way traffic simulation based on real data obtained from the annual report and DPP study xyz.
Each station has set ratio on a scale from zero to one, which indicates the probability of outgoing passengers in the station.
The lowest value has station Prosek (0.07), while the I.P. Pavlova has the highest value of (0.79) – as you can see in the chart.
Because it is a one-way simulation the first station (Letňany) has incoming passengers, so the station does not show any ratio.
Station Haje has only outgoing passengers because there is not any next station to go.
There are two time zones in the simulation - the first one is peak, which takes place in time from 7am to 9am and from 5pm to 9pm and second one dedicated to off-peak time.

Default delay between trains is set to 76 ticks.
I recommended you to try and set the biggest rank for the “big“ stations with set minimum and maximum. But as you can see – it still works.

==How to set up typical day?==
When simulation started it could be the best setup long period in the parameter add_pass_delay. I think that you know why - it‘s morning, it means less people there. After that I recommended to you goes to the high-peak gradually. If you don’t do this, some of the station will be overcrowded in high-peak meanwhile the first train goes to the end station.

= Results=
From the information obtained on the Internet, it was found that metro is almost always full at peak, which indicates the validity of this simulation model. There are about 19 metro trains per hour in the simulation, which also corresponds with a reality (in fact, there are 39 trains in peak but this value has half value because of one-way traffic simulation).

===Peak===
An analysis based on simulation, I found that if the train delay between trains is set to less than 76 or more than 81 seconds, trains start to wait in tunnel between stations to departure of the previous train. The value that avoids overcrowding station and trains are effectively filled, moves around xy seconds.
Transport capacity is about 26,900 persons per hour at peak. Simulation has only half value because of one-way traffic.

===Off-peak===
Value is reduced occurrence of new passengers (add_pass_delay) on 63 seconds during the off-peak. This was set because of fact, that there are only 12,600 passengers per hour at this time, which is 2,1 times less than at the peak.
Trains are effectively fulffiled when the values are set up to 311 second. Trains are overcrowded if the value is higher than that.

=Conslusion=
It seems that ratio which is set up today at peak is ideal. The trains If the company has set another time trains would be jammed. So 'high five' to DPP :)
At off-peak I found ideal latency between metro at value which represents 5 minutes - so it's almost identical to typical working day.

In real life is delay sometimes set up to less time than we analyzed, so it seems that company is not effective, but you know - it’s probably for increased comfort for passengers who don’t want to wait.

Model could be extended in the future - there are some possibilities like as adding depot for some trains (you know - like Kačerov where some trains terminates) or the line from station Háje to station Letňany.
And of course due to option to change number of station and a lot of variables you could build your own metro.

Ideal latency between a metro trains

2015-01-25T22:25:19Z

Xcesj04: /* Passengers at stations */

Simulation should represent what latency can be set for passagers transport in the Prague metro (depending on the density of passagers).

= Assignment =
Project Name: Ideal latency between a metro trains
Author: Bc. Jan Cestr
Software used: NetLogo
Class: 4IT496 Simulation of Systems (WS 2014/2015)

= Object =
Finding the minimum and maximum limits (time) for the Prague metro (Line C) which would reveal ideal spacing of each metro trains.
Train should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases).
It should be reckon with the fact that metro station can’t be overfull.

=What is the target of this model?=
Try to get:
1) The biggest value at the transport capacity graph
2) Minimized number of waiting passagers in stations at “passagers at stations” graph
3) Avoid the traffic jam
4) Less people at station (you will see the red flash when is overcrowded)

=Global variables=
===train_capacity===
Capacity of one train.
One graphic character depicts ten real people.

===trains_Delay===
Indicates the spacing between trains

===add_pass_delay===
Speed rate of arrival passagers

===num of stations===
Set the number of stations in model. Model is adapting scale by this value

===rank_xy===
Set the rank of outcoming passagers

==Graphs:==
===transfer capacity===
The graph show the capacity of subway per hour . There is describe that about 1440 tickes is one real hour and graph show capacity of passagers per hour. Wikipedia show that subway metro (C) transport about 26,900 per hour in high-peak – it’s nearly the same amount as in the model.

[[File:transfer_cap.jpg]]

===Passengers at stations===
Number of passagers whose waiting on train. Passagers whose leaves the train are not count in this graph.

[[File:pass.png]]

=How does the simulation work=
Each station has set a parameter stations_min stations_max which indicating the number of people who may come to the station together
(it's the random number from the specified minimum to maximum). So it‘s clear that the final station must be set to 0.
People turn red if the station is overcrowded – in this situation another people cannot come to this station.
Each passenger has set station_id that indicate the station ID which is going to get off.
Outgoing passagers are shown under the platform in the model, after a while they disappear (offcourse - station_id is not set after that).
In the station can not be two trains at one time. The train could delay in station due to large number of incoming and outgoing passager (it‘s added 0.5 tick to waiting for train departures for each one).
If this happens the following trains are waiting in the tunnel for departure from station of previous train.
User can choose attribute value station_ranks (slider rank_xx) for each station. High number represent high probability that passenger exit the train in that station.

=Model=
I developed a one-way traffic simulation based on real data obtained from the annual report and DPP study xyz.
Each station has set ratio on a scale from zero to one, which indicates the probability of outgoing passengers in the station.
The lowest value has station Prosek (0.07), while the I.P. Pavlova has the highest value of (0.79) – as you can see in the chart.
Because it is a one-way simulation the first station (Letňany) has incoming passengers, so the station does not show any ratio.
Station Haje has only outgoing passengers because there is not any next station to go.
There are two time zones in the simulation - the first one is peak, which takes place in time from 7am to 9am and from 5pm to 9pm and second one dedicated to off-peak time.

Default delay between trains is set to 76 ticks.
I recommended you to try and set the biggest rank for the “big“ stations with set minimum and maximum. But as you can see – it still works.

==How to set up typical day?==
When simulation started it could be the best setup long period in the parameter add_pass_delay. I think that you know why - it‘s morning, it means less people there. After that I recommended to you goes to the high-peak gradually. If you don’t do this, some of the station will be overcrowded in high-peak meanwhile the first train goes to the end station.

= Results=
From the information obtained on the Internet, it was found that metro is almost always full at peak, which indicates the validity of this simulation model. There are about 19 metro trains per hour in the simulation, which also corresponds with a reality (in fact, there are 39 trains in peak but this value has half value because of one-way traffic simulation).

===Peak===
An analysis based on simulation, I found that if the train delay between trains is set to less than 76 or more than 81 seconds, trains start to wait in tunnel between stations to departure of the previous train. The value that avoids overcrowding station and trains are effectively filled, moves around xy seconds.
Transport capacity is about 26,900 persons per hour at peak. Simulation has only half value because of one-way traffic.

===Off-peak===
Value is reduced occurrence of new passengers (add_pass_delay) on 63 seconds during the off-peak. This was set because of fact, that there are only 12,600 passengers per hour at this time, which is 2,1 times less than at the peak.
Trains are effectively fulffiled when the values are set up to 311 second. Trains are overcrowded if the value is higher than that.

=Conslusion=
It seems that ratio which is set up today at peak is ideal. The trains If the company has set another time trains would be jammed. So 'high five' to DPP :)
At off-peak I found ideal latency between metro at value which represents 5 minutes - so it's almost identical to typical working day.

In real life is delay sometimes set up to less time than we analyzed, so it seems that company is not effective, but you know - it’s probably for increased comfort for passengers who don’t want to wait.

Model could be extended in the future - there are some possibilities like as adding depot for some trains (you know - like Kačerov where some trains terminates) or the line from station Háje to station Letňany.
And of course due to option to change number of station and a lot of variables you could build your own metro.

File:Pass.png

2015-01-25T22:25:06Z

Xcesj04:

Ideal latency between a metro trains

2015-01-25T22:23:18Z

Xcesj04: /* transfer capacity */

Simulation should represent what latency can be set for passagers transport in the Prague metro (depending on the density of passagers).

= Assignment =
Project Name: Ideal latency between a metro trains
Author: Bc. Jan Cestr
Software used: NetLogo
Class: 4IT496 Simulation of Systems (WS 2014/2015)

= Object =
Finding the minimum and maximum limits (time) for the Prague metro (Line C) which would reveal ideal spacing of each metro trains.
Train should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases).
It should be reckon with the fact that metro station can’t be overfull.

=What is the target of this model?=
Try to get:
1) The biggest value at the transport capacity graph
2) Minimized number of waiting passagers in stations at “passagers at stations” graph
3) Avoid the traffic jam
4) Less people at station (you will see the red flash when is overcrowded)

=Global variables=
===train_capacity===
Capacity of one train.
One graphic character depicts ten real people.

===trains_Delay===
Indicates the spacing between trains

===add_pass_delay===
Speed rate of arrival passagers

===num of stations===
Set the number of stations in model. Model is adapting scale by this value

===rank_xy===
Set the rank of outcoming passagers

==Graphs:==
===transfer capacity===
The graph show the capacity of subway per hour . There is describe that about 1440 tickes is one real hour and graph show capacity of passagers per hour. Wikipedia show that subway metro (C) transport about 26,900 per hour in high-peak – it’s nearly the same amount as in the model.

[[File:transfer_cap.jpg]]

===Passengers at stations===
Number of passagers whose waiting on train. Passagers whose leaves the train are not count in this graph.

=How does the simulation work=
Each station has set a parameter stations_min stations_max which indicating the number of people who may come to the station together
(it's the random number from the specified minimum to maximum). So it‘s clear that the final station must be set to 0.
People turn red if the station is overcrowded – in this situation another people cannot come to this station.
Each passenger has set station_id that indicate the station ID which is going to get off.
Outgoing passagers are shown under the platform in the model, after a while they disappear (offcourse - station_id is not set after that).
In the station can not be two trains at one time. The train could delay in station due to large number of incoming and outgoing passager (it‘s added 0.5 tick to waiting for train departures for each one).
If this happens the following trains are waiting in the tunnel for departure from station of previous train.
User can choose attribute value station_ranks (slider rank_xx) for each station. High number represent high probability that passenger exit the train in that station.

=Model=
I developed a one-way traffic simulation based on real data obtained from the annual report and DPP study xyz.
Each station has set ratio on a scale from zero to one, which indicates the probability of outgoing passengers in the station.
The lowest value has station Prosek (0.07), while the I.P. Pavlova has the highest value of (0.79) – as you can see in the chart.
Because it is a one-way simulation the first station (Letňany) has incoming passengers, so the station does not show any ratio.
Station Haje has only outgoing passengers because there is not any next station to go.
There are two time zones in the simulation - the first one is peak, which takes place in time from 7am to 9am and from 5pm to 9pm and second one dedicated to off-peak time.

Default delay between trains is set to 76 ticks.
I recommended you to try and set the biggest rank for the “big“ stations with set minimum and maximum. But as you can see – it still works.

==How to set up typical day?==
When simulation started it could be the best setup long period in the parameter add_pass_delay. I think that you know why - it‘s morning, it means less people there. After that I recommended to you goes to the high-peak gradually. If you don’t do this, some of the station will be overcrowded in high-peak meanwhile the first train goes to the end station.

= Results=
From the information obtained on the Internet, it was found that metro is almost always full at peak, which indicates the validity of this simulation model. There are about 19 metro trains per hour in the simulation, which also corresponds with a reality (in fact, there are 39 trains in peak but this value has half value because of one-way traffic simulation).

===Peak===
An analysis based on simulation, I found that if the train delay between trains is set to less than 76 or more than 81 seconds, trains start to wait in tunnel between stations to departure of the previous train. The value that avoids overcrowding station and trains are effectively filled, moves around xy seconds.
Transport capacity is about 26,900 persons per hour at peak. Simulation has only half value because of one-way traffic.

===Off-peak===
Value is reduced occurrence of new passengers (add_pass_delay) on 63 seconds during the off-peak. This was set because of fact, that there are only 12,600 passengers per hour at this time, which is 2,1 times less than at the peak.
Trains are effectively fulffiled when the values are set up to 311 second. Trains are overcrowded if the value is higher than that.

=Conslusion=
It seems that ratio which is set up today at peak is ideal. The trains If the company has set another time trains would be jammed. So 'high five' to DPP :)
At off-peak I found ideal latency between metro at value which represents 5 minutes - so it's almost identical to typical working day.

In real life is delay sometimes set up to less time than we analyzed, so it seems that company is not effective, but you know - it’s probably for increased comfort for passengers who don’t want to wait.

Model could be extended in the future - there are some possibilities like as adding depot for some trains (you know - like Kačerov where some trains terminates) or the line from station Háje to station Letňany.
And of course due to option to change number of station and a lot of variables you could build your own metro.

File:Transfer cap.jpg

2015-01-25T22:23:00Z

Xcesj04:

Ideal latency between a metro trains

2015-01-25T22:15:50Z

Xcesj04: Created page with "Simulation should represent what latency can be set for passagers transport in the Prague metro (depending on the density of passagers). = Assignment = Project Name: Ideal..."

Simulation should represent what latency can be set for passagers transport in the Prague metro (depending on the density of passagers).

= Assignment =
Project Name: Ideal latency between a metro trains
Author: Bc. Jan Cestr
Software used: NetLogo
Class: 4IT496 Simulation of Systems (WS 2014/2015)

= Object =
Finding the minimum and maximum limits (time) for the Prague metro (Line C) which would reveal ideal spacing of each metro trains.
Train should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases).
It should be reckon with the fact that metro station can’t be overfull.

=What is the target of this model?=
Try to get:
1) The biggest value at the transport capacity graph
2) Minimized number of waiting passagers in stations at “passagers at stations” graph
3) Avoid the traffic jam
4) Less people at station (you will see the red flash when is overcrowded)

=Global variables=
===train_capacity===
Capacity of one train.
One graphic character depicts ten real people.

===trains_Delay===
Indicates the spacing between trains

===add_pass_delay===
Speed rate of arrival passagers

===num of stations===
Set the number of stations in model. Model is adapting scale by this value

===rank_xy===
Set the rank of outcoming passagers

==Graphs:==
===transfer capacity===
The graph show the capacity of subway per hour . There is describe that about 1440 tickes is one real hour and graph show capacity of passagers per hour. Wikipedia show that subway metro (C) transport about 26,900 per hour in high-peak – it’s nearly the same amount as in the model.

===Passengers at stations===
Number of passagers whose waiting on train. Passagers whose leaves the train are not count in this graph.

=How does the simulation work=
Each station has set a parameter stations_min stations_max which indicating the number of people who may come to the station together
(it's the random number from the specified minimum to maximum). So it‘s clear that the final station must be set to 0.
People turn red if the station is overcrowded – in this situation another people cannot come to this station.
Each passenger has set station_id that indicate the station ID which is going to get off.
Outgoing passagers are shown under the platform in the model, after a while they disappear (offcourse - station_id is not set after that).
In the station can not be two trains at one time. The train could delay in station due to large number of incoming and outgoing passager (it‘s added 0.5 tick to waiting for train departures for each one).
If this happens the following trains are waiting in the tunnel for departure from station of previous train.
User can choose attribute value station_ranks (slider rank_xx) for each station. High number represent high probability that passenger exit the train in that station.

=Model=
I developed a one-way traffic simulation based on real data obtained from the annual report and DPP study xyz.
Each station has set ratio on a scale from zero to one, which indicates the probability of outgoing passengers in the station.
The lowest value has station Prosek (0.07), while the I.P. Pavlova has the highest value of (0.79) – as you can see in the chart.
Because it is a one-way simulation the first station (Letňany) has incoming passengers, so the station does not show any ratio.
Station Haje has only outgoing passengers because there is not any next station to go.
There are two time zones in the simulation - the first one is peak, which takes place in time from 7am to 9am and from 5pm to 9pm and second one dedicated to off-peak time.

Default delay between trains is set to 76 ticks.
I recommended you to try and set the biggest rank for the “big“ stations with set minimum and maximum. But as you can see – it still works.

==How to set up typical day?==
When simulation started it could be the best setup long period in the parameter add_pass_delay. I think that you know why - it‘s morning, it means less people there. After that I recommended to you goes to the high-peak gradually. If you don’t do this, some of the station will be overcrowded in high-peak meanwhile the first train goes to the end station.

= Results=
From the information obtained on the Internet, it was found that metro is almost always full at peak, which indicates the validity of this simulation model. There are about 19 metro trains per hour in the simulation, which also corresponds with a reality (in fact, there are 39 trains in peak but this value has half value because of one-way traffic simulation).

===Peak===
An analysis based on simulation, I found that if the train delay between trains is set to less than 76 or more than 81 seconds, trains start to wait in tunnel between stations to departure of the previous train. The value that avoids overcrowding station and trains are effectively filled, moves around xy seconds.
Transport capacity is about 26,900 persons per hour at peak. Simulation has only half value because of one-way traffic.

===Off-peak===
Value is reduced occurrence of new passengers (add_pass_delay) on 63 seconds during the off-peak. This was set because of fact, that there are only 12,600 passengers per hour at this time, which is 2,1 times less than at the peak.
Trains are effectively fulffiled when the values are set up to 311 second. Trains are overcrowded if the value is higher than that.

=Conslusion=
It seems that ratio which is set up today at peak is ideal. The trains If the company has set another time trains would be jammed. So 'high five' to DPP :)
At off-peak I found ideal latency between metro at value which represents 5 minutes - so it's almost identical to typical working day.

In real life is delay sometimes set up to less time than we analyzed, so it seems that company is not effective, but you know - it’s probably for increased comfort for passengers who don’t want to wait.

Model could be extended in the future - there are some possibilities like as adding depot for some trains (you know - like Kačerov where some trains terminates) or the line from station Háje to station Letňany.
And of course due to option to change number of station and a lot of variables you could build your own metro.

WS 2014/2015

2015-01-25T21:25:26Z

Xcesj04: /* Simulations */

Semestral papers from winter term 2014/2015. Please, put here links to the pages with your paper. First you need to have your [[Assignments WS 2014/2015|assignment approved]].

==Simulations==

--[[User:Zhua00|Andriy Zhubryd]] 14:24, 15 January 2015 (CET) [[E-Sim Optimal Equipment Selection]]

--[[User:Xgubk00|Xgubk00]] 12:24, 17 January 2015 (CET) [[Flood evacuation]]

-- [[User:Xzasj00|Xzasj00]] 00:07, 18 January 2015 (CET) [[Formula 1 teams economic situation]]

-- [[User:Qnovm21|Qnovm21]] 10:33, 18 January 2015 (CET) [[Simulation of the surgery staff in a hospital]]

-- [[User:Xzigm03|Xzigm03]] 23:40, 18 January 2015 (CET) [[Poker probabilities and variance simulation]]

-- [[User:Xkraj119|Xkraj119]] 14:41, 24 January 2015 (CET) [[Software Support Lifecycle]]

-- [[User:Xcesj04|Xcesj04]] 23:00, 25 January 2015 (CET) [[Ideal latency between a metro trains]]

==Papers==

--[[User:Xgubk00|Xgubk00]] 12:24, 17 January 2015 (CET) [[Game theory]]

--[[User:Qnovm21|Qnovm21]] 16:40, 21 January 2015 (CET) [[Causal loop diagram]]

--[[User:Xkraj119|Xkraj119]] 10:32, 24 January 2015 (CET) [https://en.wikipedia.org/wiki/Growth_and_underinvestment Growth and Underinvestment Archetype]

--[[User:Xzasj00|Xzasj00]] 18:57, 24 January 2015 (CET) [https://en.wikipedia.org/wiki/Escalation_Archetype Escalation Archetype]

Xcesj04

2014-12-11T23:57:28Z

Xcesj04: /* Global variables */

= Ideal latency between a metro trains =
Simulation should represent what latency can be set for passenger transport in the Prague metro (depending on the density of passengers).

= Assignment =
*'''Project Name:''' Ideal latency between a metro trains
*'''Author:''' Bc. Jan Cestr
*'''Software used:''' NetLogo

= Object =
Finding the minimum and maximum limits (time) for the Prague metro (Line C) which would reveal ideal spacing of each metro trains.
Train should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases). It should be reckon with the fact that metro station can’t be overfull.

= Global variables =
* '''Time latency between each metro trains'''
* '''Number of passengers in the station (more people in rush-hour than off-peak hours)'''
* '''Frequency of people who choose to travel by metro (depending on location)'''
* '''Throughput'''
* '''Transport capacity of metro'''

= Outcome =
Simulation to determine the ideal spacing (latency) between trains - ideal ratio between the number of passengers and the spacing of trains (boundary between traffic jams and traffic collaps because of overfull stations.

Xcesj04

2014-12-11T23:56:37Z

Xcesj04: /* Object */

= Ideal latency between a metro trains =
Simulation should represent what latency can be set for passenger transport in the Prague metro (depending on the density of passengers).

= Assignment =
*'''Project Name:''' Ideal latency between a metro trains
*'''Author:''' Bc. Jan Cestr
*'''Software used:''' NetLogo

= Object =
Finding the minimum and maximum limits (time) for the Prague metro (Line C) which would reveal ideal spacing of each metro trains.
Train should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases). It should be reckon with the fact that metro station can’t be overfull.

= Global variables =
Time latency between each metro trains
Number of passengers in the station (more people in rush-hour than off-peak hours)
Frequency of people who choose to travel by metro (depending on location)
Throughput
Transport capacity of metro

= Outcome =
Simulation to determine the ideal spacing (latency) between trains - ideal ratio between the number of passengers and the spacing of trains (boundary between traffic jams and traffic collaps because of overfull stations.

Xcesj04

2014-12-11T23:52:41Z

Xcesj04: /* Global variables */

= Ideal latency between a metro trains =
Simulation should represent what latency can be set for passenger transport in the Prague metro (depending on the density of passengers).

= Assignment =
*'''Project Name:''' Ideal latency between a metro trains
*'''Author:''' Bc. Jan Cestr
*'''Software used:''' NetLogo

= Object =
Finding the minimum and maximum limits (time) for the Prague metro which would reveal the most ideal spacing of each metro trains.
should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases). It should be reckon with the fact that metro station can’t be overfull.

= Global variables =
Time latency between each metro trains
Number of passengers in the station (more people in rush-hour than off-peak hours)
Frequency of people who choose to travel by metro (depending on location)
Throughput
Transport capacity of metro

= Outcome =
Simulation to determine the ideal spacing (latency) between trains - ideal ratio between the number of passengers and the spacing of trains (boundary between traffic jams and traffic collaps because of overfull stations.

Xcesj04

2014-12-11T23:50:35Z

Xcesj04:

= Ideal latency between a metro trains =
Simulation should represent what latency can be set for passenger transport in the Prague metro (depending on the density of passengers).

= Assignment =
*'''Project Name:''' Ideal latency between a metro trains
*'''Author:''' Bc. Jan Cestr
*'''Software used:''' NetLogo

= Object =
Finding the minimum and maximum limits (time) for the Prague metro which would reveal the most ideal spacing of each metro trains.
should not stop in the tunnel due to waiting for the previous train (apart from exceptional cases). It should be reckon with the fact that metro station can’t be overfull.

= Global variables =
Time latency between each metro trains.
Number of passengers in the station (more people in rush-hour than off-peak hours)
Frequency of people who choose to travel by metro (depending on location)
Throughput
Transport capacity of metro

= Outcome =
Simulation to determine the ideal spacing (latency) between trains - ideal ratio between the number of passengers and the spacing of trains (boundary between traffic jams and traffic collaps because of overfull stations.

Xcesj04

2014-12-11T23:44:13Z

Xcesj04: moved Xcesj04 old to Xcesj04 over redirect

#REDIRECT [[Xcesj04 old one]]

Xcesj04 old

2014-12-11T23:44:13Z

Xcesj04: moved Xcesj04 old to Xcesj04 over redirect

#REDIRECT [[Xcesj04]]

Xcesj04 old one

2014-12-11T23:43:13Z

Xcesj04: moved Xcesj04 old to Xcesj04 old one

== Ideální časová latence mezi jednotlivými soupravami metra ==

Simulace by měla znázorňovat, jakou časovou latenci je možno nastavit pro přepravu cestujících v pražském metru (v závislosti na hustotě cestujících).

== Zadání: ==
Název simulace: Ideální časová latence mezi jednotlivými soupravami metra

Autor: Bc. Jan Cestr

Modelovací nástroj: NetLogo

== Cíl: ==
Nalezení nejnižší a nejvyšší meze (času) pro linku pražského metra, která by prozradila nejideálnější rozestup jednotlivých souprav metra. Soupravy by se neměly v tunelu „zasekávat“ z důvodu čekání na předešlou soupravu (až na výjimečné případy). Rovněž je také nutné počítat s tím, že stanice metra nesmí být přelidněná.

== Proměnné ==
Čas mezi jednotlivými soupravami metra

Počet lidí ve stanici (ve špičce cestuje více lidí než mimo špičku)

Četnost objevování lidí, kteří se rozhodnou cestovat metrem (v závislosti na lokalitě)

Propustnost

Přepravní kapacita metra

== Výstup: ==
Výstupem bude simulace, která nalezne nejideálnější rozestup časovou latenci mezi jednotlivými soupravami metra takovou, jež nabídne ideální poměr mezi počtem přepravených cestujících a rozestupy mezi vlaky (hranice mezi zasekáváním v tunelu a dopravním kolapsem, kvůli přehlednosti nástupišť).

'''Schváleno'''. [[User:Tomáš|Tomáš]] 14:31, 11 May 2014 (CEST)

Xcesj04

2014-12-11T23:43:13Z

Xcesj04: moved Xcesj04 old to Xcesj04 old one

#REDIRECT [[Xcesj04 old one]]

Xcesj04 old one

2014-12-11T23:42:20Z

Xcesj04: moved Xcesj04 to Xcesj04 old

Assignments WS 2014/2015

2014-12-11T23:39:49Z

Xcesj04: /* Assignments */

{{DISPLAYTITLE:Assignments WS 2014/2015}}

{{Ambox
| text = <div>
Please, put here your assignments. Do not forget to sign them. You can use <nowiki>~~~~</nowiki> (four tildas) for an automatic signature. Use Show preview in order to check the result before your final sumbition.
</div>
}}

{{Ambox
| text = <div>
Please, strive to formulate your assignment carefully. We expect an adequate effort to formulate the assignment as it is your semestral paper. Do not forget that your main goal is a research paper. It means your simulation model must generate the results that are specific, measurable and verifiable. Think twice how you will develop your model, which entities you will use, draw a model diagram, consider what you will measure. No sooner than when you have a good idea about the model, submit your assignment. And of course, read [[How to deal with the simulation assignment/en|How to deal with the simulation assignment]].
</div>
}}

{{Ambox
| type = content
| text = <div>
In order to avoid possible confusion, please, check if you have added '''approved''' in bold somewhere in our comment under your submission. If there is no '''approved''', it means the assignment was not approved yet.
</div>
}}

== Assignments ==
[[xcesj04 ]]

Assignments WS 2014/2015

2014-12-11T23:39:14Z

Xcesj04: /* Assignments */

File:Model met.png

2014-06-15T21:44:48Z

Xcesj04: