Simulace.info - User contributions [en]

Indian Elephant Population in Thailand

2020-01-20T22:51:14Z

Xkavj12: /* Conclusion */

=Problem definition=
During the course of the 20th century, the population of indian elephants has decreased drastically, mostly due to a significant reduction of elephants' natural habitat, as well as decrease in utilization of elephants in logging industry and shift to a role of a tourist attraction.
This model showcases the evolution of elephants' population in Thailand for upcoming 100 years.

=Method=
The vensim modelling tool was selected for the purpose of this simulation.

=Model=
[[File:Thai_elepahnat_model.PNG]]
==Model variables==
===Population===
Number of elephants in Thailand. Starting value is 8900 <ref name="fao">ROGER, L. The elephant situation in Thailand and a plea for co-operation[online]. Available from: http://www.fao.org/3/ad031e/ad031e0r.htm </ref>. This is the variable that we are examining.

===Increase===
Number of elephants that are born 
=Natality*Population
===Decrease===
Number of elephants that have died 
=Mortality*Population
===Natality===
Ratio of newly born elephants to elephant population. Amount of newborn elephants equals fertility multiplied by number of females in reproductive age divided by 40*2 (number of reproductive years, multiplied by 2 as elephants pregnancy takes 22-24 months). <ref name="reproduction">Elephant Reproduction [online]. Available from: https://www.elephant-world.com/elephant-reproduction/</ref> We then multiply by Governement regualtion ratio. 
=((Fertility*((Ratio of females*Population)*Ratio of females in reproductive age)/80)*Government regulations)/Population
===Fertility===
Amount of calves a female is able to have during her reproductive lifespan. 40% of elephants' population lives in wilderness and the fertility is not affected by stress therefore a wild female is able to have 10 calves, and semi-domesticated female is able to have 7 calves during her life.<ref name="reproduction"/> 
=0.4*10+0.6*7

===Ratio of females in reproductive age===
Elephant female can have calves during her 15 to 50 years. <ref name="reproduction"/> 
=0.5714
===Ratio of females===
Ratio of females on elephants' population<ref name="fao"/> 
=0.53476
===Government regulation===
Index of government regulations <0;1>, 1 means no government regulation 
=1
===Mortality===
Ratio of dead elephants on the elephants' population. 
=((Population/Average lifespan) + Unnatural deaths)/Population
===Average lifespan===
=70
===Unnatural deaths===
Number of deaths that do not happen naturally. 
=((Deaths by improper handling ratio*Population)+(Poaching ratio*Population))*Government regulations + Population*Deforestation ratio
===Deaths by improper handling ratio===
Ratio of deaths that happen due to unhuman behavior towards elephants and conditions they have to live in.<ref name="seaworld">Longevity and causes of death [online]. Available from: https://seaworld.org/animals/all-about/elephants/longevity/</ref> 
=0.01685

===Poaching ratio===
Ratio of deaths that happen because of elephants being hunted either for skin, tusks or to capture young calve.<ref name="seaworld" /> 
=3.3e-05
===Deforestation ratio===
Ratio of deforastation in Thailand, this has a close correlation to number of elephants as this the major factor affecting the population. <ref name="forest">Deforestation statistics for Thailand [online]. Available from: https://rainforests.mongabay.com/deforestation/archive/Thailand.htm</ref> 
=0.0035

=Results=
[[File:Thai elephant graph.PNG]]
[[File:Thai elephant table.PNG]]
 
As we can see, we can expect a continuous decrease in elephants' population in Thailand. By the year 2119 the elephants' population in Thailand should decrease by 2492 elephants.

=Conclusion=
In this simulation I created a functional model representing the evolution of elephants' population in Thailand. The results show continuous decrease over the course of following 100 years. However there is a room for improvements, like parameter deforestation ratio because nowadays the problem of deforestation is gaining on significance in general public eyes and this might lead into deforestation ratio decrease and potentially lead into elephants' population growth. In addition, also the pressure from general public as well as organizations like WWF might lead into more strict government regulations.

=Code=
[[File:Elephant population.mdl]]

=References=
<references/>

Indian Elephant Population in Thailand

2020-01-20T22:49:50Z

Xkavj12: /* Model variables */

=Problem definition=
During the course of the 20th century, the population of indian elephants has decreased drastically, mostly due to a significant reduction of elephants' natural habitat, as well as decrease in utilization of elephants in logging industry and shift to a role of a tourist attraction.
This model showcases the evolution of elephants' population in Thailand for upcoming 100 years.

=Method=
The vensim modelling tool was selected for the purpose of this simulation.

=Model=
[[File:Thai_elepahnat_model.PNG]]
==Model variables==
===Population===
Number of elephants in Thailand. Starting value is 8900 <ref name="fao">ROGER, L. The elephant situation in Thailand and a plea for co-operation[online]. Available from: http://www.fao.org/3/ad031e/ad031e0r.htm </ref>. This is the variable that we are examining.

===Increase===
Number of elephants that are born 
=Natality*Population
===Decrease===
Number of elephants that have died 
=Mortality*Population
===Natality===
Ratio of newly born elephants to elephant population. Amount of newborn elephants equals fertility multiplied by number of females in reproductive age divided by 40*2 (number of reproductive years, multiplied by 2 as elephants pregnancy takes 22-24 months). <ref name="reproduction">Elephant Reproduction [online]. Available from: https://www.elephant-world.com/elephant-reproduction/</ref> We then multiply by Governement regualtion ratio. 
=((Fertility*((Ratio of females*Population)*Ratio of females in reproductive age)/80)*Government regulations)/Population
===Fertility===
Amount of calves a female is able to have during her reproductive lifespan. 40% of elephants' population lives in wilderness and the fertility is not affected by stress therefore a wild female is able to have 10 calves, and semi-domesticated female is able to have 7 calves during her life.<ref name="reproduction"/> 
=0.4*10+0.6*7

===Ratio of females in reproductive age===
Elephant female can have calves during her 15 to 50 years. <ref name="reproduction"/> 
=0.5714
===Ratio of females===
Ratio of females on elephants' population<ref name="fao"/> 
=0.53476
===Government regulation===
Index of government regulations <0;1>, 1 means no government regulation 
=1
===Mortality===
Ratio of dead elephants on the elephants' population. 
=((Population/Average lifespan) + Unnatural deaths)/Population
===Average lifespan===
=70
===Unnatural deaths===
Number of deaths that do not happen naturally. 
=((Deaths by improper handling ratio*Population)+(Poaching ratio*Population))*Government regulations + Population*Deforestation ratio
===Deaths by improper handling ratio===
Ratio of deaths that happen due to unhuman behavior towards elephants and conditions they have to live in.<ref name="seaworld">Longevity and causes of death [online]. Available from: https://seaworld.org/animals/all-about/elephants/longevity/</ref> 
=0.01685

===Poaching ratio===
Ratio of deaths that happen because of elephants being hunted either for skin, tusks or to capture young calve.<ref name="seaworld" /> 
=3.3e-05
===Deforestation ratio===
Ratio of deforastation in Thailand, this has a close correlation to number of elephants as this the major factor affecting the population. <ref name="forest">Deforestation statistics for Thailand [online]. Available from: https://rainforests.mongabay.com/deforestation/archive/Thailand.htm</ref> 
=0.0035

=Results=
[[File:Thai elephant graph.PNG]]
[[File:Thai elephant table.PNG]]
 
As we can see, we can expect a continuous decrease in elephants' population in Thailand. By the year 2119 the elephants' population in Thailand should decrease by 2492 elephants.

=Conclusion=
In this simulation I created a functional model representing the evolution of elephants' population in Thailand. The results show continuous decrease over the course of following 100 years. However there is a room for improvements, like parameter deforestation ratio because nowadays the problem of deforestation is gaining on significance in general public eyes and this might lead into deforestation ratio decrease and potentially lead into elephants' population growth.

=Code=
[[File:Elephant population.mdl]]

=References=
<references/>

WS 2019/2020

2020-01-20T22:48:40Z

Xkavj12: /* Simulation */

Semestral papers from winter term 2019/2020. Please, put here links to the pages with your paper. First you need to have your [[Assignments WS 2019/2020|assignment approved]]

== Simulation ==
[http://www.simulace.info/index.php/Cotton_Processing_Quality:_Cotton,_Seed,_Lint,_Trash Cotton Processing Quality: Cotton, Seed, Lint, Trash] , Ibrahim Aghazada (in progress)

[http://www.simulace.info/index.php/Time_Series_Model_Building_Process Time Series Model Building Process] , Nikola Hažmuková

[http://www.simulace.info/index.php/Indian_Elephant_Population_in_Thailand Indian Elephant Population in Thailand] , [[User:Xkavj12|Xkavj12]] ([[User talk:Xkavj12|talk]]) 18:42, 20 January 2020 (CET)

[http://www.simulace.info/index.php/Atlantic_Bluefin_Tuna_Population Atlantic Bluefin Tuna Population], [[User:Vokp00|Vokp00]] ([[User talk:Vokp00|talk]]) 20:32, 20 January 2020 (CET)

[http://www.simulace.info/index.php/Shopping_Centre_Simulation Shopping Centre Management Simulation], [[User:Tkad01|Tkad01]] ([[User talk:Tkad01|talk]]) 21:57, 20 January 2020 (CET) (in progress)

== Textbook Chapters ==
[http://www.simulace.info/index.php/Limits_to_Growth Limits to Growth] , Ibrahim Aghazada (in progress)

Indian Elephant Population in Thailand

2020-01-20T22:39:56Z

Xkavj12: /* Fertility */

=Problem definition=
During the course of the 20th century, the population of indian elephants has decreased drastically, mostly due to a significant reduction of elephants' natural habitat, as well as decrease in utilization of elephants in logging industry and shift to a role of a tourist attraction.
This model showcases the evolution of elephants' population in Thailand for upcoming 100 years.

=Method=
The vensim modelling tool was selected for the purpose of this simulation.

=Model=
[[File:Thai_elepahnat_model.PNG]]
==Model variables==
===Population===
Number of elephants in Thailand. Starting value is 8900 <ref name="fao">ROGER, L. The elephant situation in Thailand and a plea for co-operation[online]. Available from: http://www.fao.org/3/ad031e/ad031e0r.htm </ref>. This is the variable that we are examining.

===Increase===
Number of elephants that are born 
=Natality*Population
===Decrease===
Number of elephants that have died 
=Mortality*Population
===Natality===
Ratio of newly born elephants to elephant population. Amount of newborn elephants equals fertility multiplied by number of females in reproductive age divided by 40*2 (number of reproductive years, multiplied by 2 as elephants pregnancy takes 22-24 months). <ref name="reproduction">Elephant Reproduction [online]. Available from: https://www.elephant-world.com/elephant-reproduction/</ref> We then multiply by Governement regualtion ratio. 
=((Fertility*((Ratio of females*Population)*Ratio of females in reproductive age)/80)*Government regulations)/Population
===Fertility===
Amount of calves a female is able to have during her reproductive lifespan. 40% of elephants' population lives in wilderness and the fertility is not affected by stress therefore a wild female is able to have 10 calves, and semi-domesticated female is able to have 7 calves during her life.<ref name="reproduction"/> 
=0.4*10+0.6*7

===Ratio of females in reproductive age===
Elephant female can have calves during her 15 to 50 years. <ref name="reproduction"/> 
=0.5714
===Ratio of females===
Ratio of females on elephants' population<ref name="fao"/> 
=0.53476
===Government regulation===
Index of government regulations <0;1>, 1 means no government regulation 
=1
===Mortality===
Ratio of dead elephants on the elephants' population. 
=((Population/Average lifespan) + Unnatural deaths)/Population
===Average lifespan===
=70
===Unnatural deaths===
Number of deaths that do not happen naturally 
=((Deaths by improper handling ratio*Population)+(Poaching ratio*Population))*Government regulations + Population*Deforestation ratio
===Deaths by improper handling ratio===
Ratio of deaths that happen due to unhuman behavior towards elephants and conditions they have to live in<ref name="seaworld">Longevity and causes of death [online]. Available from: https://seaworld.org/animals/all-about/elephants/longevity/</ref> 
=0.01685

===Poaching ratio===
Ratio of deaths that happen because of elephants being hunted either for skin, tusks or to capture young calve<ref name="seaworld" /> 
=3.3e-05
===Deforestation ratio===
Ratio of deforastation in Thailand, this has a close correlation to number of elephants as this the major factor affecting the population <ref name="forest">Deforestation statistics for Thailand [online]. Available from: https://rainforests.mongabay.com/deforestation/archive/Thailand.htm</ref> 
=0.0035

=Results=
[[File:Thai elephant graph.PNG]]
[[File:Thai elephant table.PNG]]
 
As we can see, we can expect a continuous decrease in elephants' population in Thailand. By the year 2119 the elephants' population in Thailand should decrease by 2492 elephants.

=Conclusion=
In this simulation I created a functional model representing the evolution of elephants' population in Thailand. The results show continuous decrease over the course of following 100 years. However there is a room for improvements, like parameter deforestation ratio because nowadays the problem of deforestation is gaining on significance in general public eyes and this might lead into deforestation ratio decrease and potentially lead into elephants' population growth.

=Code=
[[File:Elephant population.mdl]]

=References=
<references/>

Indian Elephant Population in Thailand

2020-01-20T22:38:52Z

Xkavj12: /* Population */

=Problem definition=
During the course of the 20th century, the population of indian elephants has decreased drastically, mostly due to a significant reduction of elephants' natural habitat, as well as decrease in utilization of elephants in logging industry and shift to a role of a tourist attraction.
This model showcases the evolution of elephants' population in Thailand for upcoming 100 years.

=Method=
The vensim modelling tool was selected for the purpose of this simulation.

=Model=
[[File:Thai_elepahnat_model.PNG]]
==Model variables==
===Population===
Number of elephants in Thailand. Starting value is 8900 <ref name="fao">ROGER, L. The elephant situation in Thailand and a plea for co-operation[online]. Available from: http://www.fao.org/3/ad031e/ad031e0r.htm </ref>. This is the variable that we are examining.

===Increase===
Number of elephants that are born 
=Natality*Population
===Decrease===
Number of elephants that have died 
=Mortality*Population
===Natality===
Ratio of newly born elephants to elephant population. Amount of newborn elephants equals fertility multiplied by number of females in reproductive age divided by 40*2 (number of reproductive years, multiplied by 2 as elephants pregnancy takes 22-24 months). <ref name="reproduction">Elephant Reproduction [online]. Available from: https://www.elephant-world.com/elephant-reproduction/</ref> We then multiply by Governement regualtion ratio. 
=((Fertility*((Ratio of females*Population)*Ratio of females in reproductive age)/80)*Government regulations)/Population
===Fertility===
Amount of calves a female is able to have during her reproductive lifespan. 40% of elephants' population lives in wilderness and the fertility is not affected by stress therefore a wild female is able to have 10 calves, and semi-domesticated female is able to have 7 <ref name="reproduction"/> 
=0.4*10+0.6*7
===Ratio of females in reproductive age===
Elephant female can have calves during her 15 to 50 years. <ref name="reproduction"/> 
=0.5714
===Ratio of females===
Ratio of females on elephants' population<ref name="fao"/> 
=0.53476
===Government regulation===
Index of government regulations <0;1>, 1 means no government regulation 
=1
===Mortality===
Ratio of dead elephants on the elephants' population. 
=((Population/Average lifespan) + Unnatural deaths)/Population
===Average lifespan===
=70
===Unnatural deaths===
Number of deaths that do not happen naturally 
=((Deaths by improper handling ratio*Population)+(Poaching ratio*Population))*Government regulations + Population*Deforestation ratio
===Deaths by improper handling ratio===
Ratio of deaths that happen due to unhuman behavior towards elephants and conditions they have to live in<ref name="seaworld">Longevity and causes of death [online]. Available from: https://seaworld.org/animals/all-about/elephants/longevity/</ref> 
=0.01685

===Poaching ratio===
Ratio of deaths that happen because of elephants being hunted either for skin, tusks or to capture young calve<ref name="seaworld" /> 
=3.3e-05
===Deforestation ratio===
Ratio of deforastation in Thailand, this has a close correlation to number of elephants as this the major factor affecting the population <ref name="forest">Deforestation statistics for Thailand [online]. Available from: https://rainforests.mongabay.com/deforestation/archive/Thailand.htm</ref> 
=0.0035

=Results=
[[File:Thai elephant graph.PNG]]
[[File:Thai elephant table.PNG]]
 
As we can see, we can expect a continuous decrease in elephants' population in Thailand. By the year 2119 the elephants' population in Thailand should decrease by 2492 elephants.

=Conclusion=
In this simulation I created a functional model representing the evolution of elephants' population in Thailand. The results show continuous decrease over the course of following 100 years. However there is a room for improvements, like parameter deforestation ratio because nowadays the problem of deforestation is gaining on significance in general public eyes and this might lead into deforestation ratio decrease and potentially lead into elephants' population growth.

=Code=
[[File:Elephant population.mdl]]

=References=
<references/>

Indian Elephant Population in Thailand

2020-01-20T22:36:37Z

Xkavj12: /* Ratio of females */

=Problem definition=
During the course of the 20th century, the population of indian elephants has decreased drastically, mostly due to a significant reduction of elephants' natural habitat, as well as decrease in utilization of elephants in logging industry and shift to a role of a tourist attraction.
This model showcases the evolution of elephants' population in Thailand for upcoming 100 years.

=Method=
The vensim modelling tool was selected for the purpose of this simulation.

=Model=
[[File:Thai_elepahnat_model.PNG]]
==Model variables==
===Population===
Number of elephants in Thailand. Starting value 8900 <ref name="fao">ROGER, L. The elephant situation in Thailand and a plea for co-operation[online]. Available from: http://www.fao.org/3/ad031e/ad031e0r.htm </ref>. This is the variable that we are examining.
===Increase===
Number of elephants that are born 
=Natality*Population
===Decrease===
Number of elephants that have died 
=Mortality*Population
===Natality===
Ratio of newly born elephants to elephant population. Amount of newborn elephants equals fertility multiplied by number of females in reproductive age divided by 40*2 (number of reproductive years, multiplied by 2 as elephants pregnancy takes 22-24 months). <ref name="reproduction">Elephant Reproduction [online]. Available from: https://www.elephant-world.com/elephant-reproduction/</ref> We then multiply by Governement regualtion ratio. 
=((Fertility*((Ratio of females*Population)*Ratio of females in reproductive age)/80)*Government regulations)/Population
===Fertility===
Amount of calves a female is able to have during her reproductive lifespan. 40% of elephants' population lives in wilderness and the fertility is not affected by stress therefore a wild female is able to have 10 calves, and semi-domesticated female is able to have 7 <ref name="reproduction"/> 
=0.4*10+0.6*7
===Ratio of females in reproductive age===
Elephant female can have calves during her 15 to 50 years. <ref name="reproduction"/> 
=0.5714
===Ratio of females===
Ratio of females on elephants' population<ref name="fao"/> 
=0.53476
===Government regulation===
Index of government regulations <0;1>, 1 means no government regulation 
=1
===Mortality===
Ratio of dead elephants on the elephants' population. 
=((Population/Average lifespan) + Unnatural deaths)/Population
===Average lifespan===
=70
===Unnatural deaths===
Number of deaths that do not happen naturally 
=((Deaths by improper handling ratio*Population)+(Poaching ratio*Population))*Government regulations + Population*Deforestation ratio
===Deaths by improper handling ratio===
Ratio of deaths that happen due to unhuman behavior towards elephants and conditions they have to live in<ref name="seaworld">Longevity and causes of death [online]. Available from: https://seaworld.org/animals/all-about/elephants/longevity/</ref> 
=0.01685

===Poaching ratio===
Ratio of deaths that happen because of elephants being hunted either for skin, tusks or to capture young calve<ref name="seaworld" /> 
=3.3e-05
===Deforestation ratio===
Ratio of deforastation in Thailand, this has a close correlation to number of elephants as this the major factor affecting the population <ref name="forest">Deforestation statistics for Thailand [online]. Available from: https://rainforests.mongabay.com/deforestation/archive/Thailand.htm</ref> 
=0.0035

=Results=
[[File:Thai elephant graph.PNG]]
[[File:Thai elephant table.PNG]]
 
As we can see, we can expect a continuous decrease in elephants' population in Thailand. By the year 2119 the elephants' population in Thailand should decrease by 2492 elephants.

=Conclusion=
In this simulation I created a functional model representing the evolution of elephants' population in Thailand. The results show continuous decrease over the course of following 100 years. However there is a room for improvements, like parameter deforestation ratio because nowadays the problem of deforestation is gaining on significance in general public eyes and this might lead into deforestation ratio decrease and potentially lead into elephants' population growth.

=Code=
[[File:Elephant population.mdl]]

=References=
<references/>

Indian Elephant Population in Thailand

2020-01-20T22:35:57Z

Xkavj12: /* Model variables */

=Problem definition=
During the course of the 20th century, the population of indian elephants has decreased drastically, mostly due to a significant reduction of elephants' natural habitat, as well as decrease in utilization of elephants in logging industry and shift to a role of a tourist attraction.
This model showcases the evolution of elephants' population in Thailand for upcoming 100 years.

=Method=
The vensim modelling tool was selected for the purpose of this simulation.

=Model=
[[File:Thai_elepahnat_model.PNG]]
==Model variables==
===Population===
Number of elephants in Thailand. Starting value 8900 <ref name="fao">ROGER, L. The elephant situation in Thailand and a plea for co-operation[online]. Available from: http://www.fao.org/3/ad031e/ad031e0r.htm </ref>. This is the variable that we are examining.
===Increase===
Number of elephants that are born 
=Natality*Population
===Decrease===
Number of elephants that have died 
=Mortality*Population
===Natality===
Ratio of newly born elephants to elephant population. Amount of newborn elephants equals fertility multiplied by number of females in reproductive age divided by 40*2 (number of reproductive years, multiplied by 2 as elephants pregnancy takes 22-24 months). <ref name="reproduction">Elephant Reproduction [online]. Available from: https://www.elephant-world.com/elephant-reproduction/</ref> We then multiply by Governement regualtion ratio. 
=((Fertility*((Ratio of females*Population)*Ratio of females in reproductive age)/80)*Government regulations)/Population
===Fertility===
Amount of calves a female is able to have during her reproductive lifespan. 40% of elephants' population lives in wilderness and the fertility is not affected by stress therefore a wild female is able to have 10 calves, and semi-domesticated female is able to have 7 <ref name="reproduction"/> 
=0.4*10+0.6*7
===Ratio of females in reproductive age===
Elephant female can have calves during her 15 to 50 years. <ref name="reproduction"/> 
=0.5714
===Ratio of females===
Ratio of females on elephants' population<ref name="fao"> 
=0.53476
===Government regulation===
Index of government regulations <0;1>, 1 means no government regulation 
=1
===Mortality===
Ratio of dead elephants on the elephants' population. 
=((Population/Average lifespan) + Unnatural deaths)/Population
===Average lifespan===
=70
===Unnatural deaths===
Number of deaths that do not happen naturally 
=((Deaths by improper handling ratio*Population)+(Poaching ratio*Population))*Government regulations + Population*Deforestation ratio
===Deaths by improper handling ratio===
Ratio of deaths that happen due to unhuman behavior towards elephants and conditions they have to live in<ref name="seaworld">Longevity and causes of death [online]. Available from: https://seaworld.org/animals/all-about/elephants/longevity/</ref> 
=0.01685
===Poaching ratio===
Ratio of deaths that happen because of elephants being hunted either for skin, tusks or to capture young calve<ref name="seaworld" /> 
=3.3e-05
===Deforestation ratio===
Ratio of deforastation in Thailand, this has a close correlation to number of elephants as this the major factor affecting the population <ref name="forest">Deforestation statistics for Thailand [online]. Available from: https://rainforests.mongabay.com/deforestation/archive/Thailand.htm</ref> 
=0.0035

=Results=
[[File:Thai elephant graph.PNG]]
[[File:Thai elephant table.PNG]]
 
As we can see, we can expect a continuous decrease in elephants' population in Thailand. By the year 2119 the elephants' population in Thailand should decrease by 2492 elephants.

=Conclusion=
In this simulation I created a functional model representing the evolution of elephants' population in Thailand. The results show continuous decrease over the course of following 100 years. However there is a room for improvements, like parameter deforestation ratio because nowadays the problem of deforestation is gaining on significance in general public eyes and this might lead into deforestation ratio decrease and potentially lead into elephants' population growth.

=Code=
[[File:Elephant population.mdl]]

=References=
<references/>

Indian Elephant Population in Thailand

2020-01-20T22:24:42Z

Xkavj12:

=Problem definition=
During the course of the 20th century, the population of indian elephants has decreased drastically, mostly due to a significant reduction of elephants' natural habitat, as well as decrease in utilization of elephants in logging industry and shift to a role of a tourist attraction.
This model showcases the evolution of elephants' population in Thailand for upcoming 100 years.

=Method=
The vensim modelling tool was selected for the purpose of this simulation.

=Model=
[[File:Thai_elepahnat_model.PNG]]
==Model variables==
===Population===
Number of elephants in Thailand. Starting value 8900. This is the variable that we are examining.
===Increase===
Number of elephants that are born 
=Natality*Population
===Decrease===
Number of elephants that have died 
=Mortality*Population
===Natality===
Ratio of newly born elephants to elephant population. Amount of newborn elephants equals fertility multiplied by number of females in reproductive age divided by 40*2 (number of reproductive years, multiplied by 2 as elephants pregnancy takes 22-24 months). We then multiply by Governement regualtion ratio. 
=((Fertility*((Ratio of females*Population)*Ratio of females in reproductive age)/80)*Government regulations)/Population
===Fertility===
Amount of calves a female is able to have during her reproductive lifespan. 40% of elephants' population lives in wilderness and the fertility is not affected by stress therefore a wild female is able to have 10 calves, and semi-domesticated female is able to have 7 
=0.4*10+0.6*7
===Ratio of females in reproductive age===
Elephant female can have calves during her 15 to 50 years. 
=0.5714
===Ratio of females===
Ratio of females on elephants' population 
=53476
===Government regulation===
Index of government regulations <0;1>, 1 means no government regulation 
=1
===Mortality===
Ratio of dead elephants on the elephants' population. 
=((Population/Average lifespan) + Unnatural deaths)/Population
===Average lifespan===
=70
===Unnatural deaths===
Number of deaths that do not happen naturally 
=((Deaths by improper handling ratio*Population)+(Poaching ratio*Population))*Government regulations + Population*Deforestation ratio
===Deaths by improper handling ratio===
Ratio of deaths that happen due to unhuman behavior towards elephants and conditions they have to live in 
=0.01685
===Poaching ratio===
Ratio of deaths that happen because of elephants being hunted either for skin, tusks or to capture young calve 
=3.3e-05
===Deforestation ratio===
Ratio of deforastation in Thailand, this has a close correlation to number of elephants as this the major factor affecting the population 
=0.0035

=Results=
[[File:Thai elephant graph.PNG]]
[[File:Thai elephant table.PNG]]
 
As we can see, we can expect a continuous decrease in elephants' population in Thailand. By the year 2119 the elephants' population in Thailand should decrease by 2492 elephants.

=Conclusion=
In this simulation I created a functional model representing the evolution of elephants' population in Thailand. The results show continuous decrease over the course of following 100 years. However there is a room for improvements, like parameter deforestation ratio because nowadays the problem of deforestation is gaining on significance in general public eyes and this might lead into deforestation ratio decrease and potentially lead into elephants' population growth.

=Code=
[[File:Elephant population.mdl]]

=References=
<references/>

Indian Elephant Population in Thailand

2020-01-20T22:20:26Z

Xkavj12: /* Code */

Introduction

=Problem definition=
During the course of the 20th century, the population of indian elephants has decreased drastically, mostly due to a significant reduction of elephants' natural habitat, as well as decrease in utilization of elephants in logging industry and shift to a role of a tourist attraction.
This model showcases the evolution of elephants' population in Thailand for upcoming 100 years.

=Method=
The vensim modelling tool was selected for the purpose of this simulation.

=Model=
[[File:Thai_elepahnat_model.PNG]]
==Model variables==
===Population===
Number of elephants in Thailand. Starting value 8900. This is the variable that we are examining.
===Increase===
Number of elephants that are born 
=Natality*Population
===Decrease===
Number of elephants that have died 
=Mortality*Population
===Natality===
Ratio of newly born elephants to elephant population. Amount of newborn elephants equals fertility multiplied by number of females in reproductive age divided by 40*2 (number of reproductive years, multiplied by 2 as elephants pregnancy takes 22-24 months). We then multiply by Governement regualtion ratio. 
=((Fertility*((Ratio of females*Population)*Ratio of females in reproductive age)/80)*Government regulations)/Population
===Fertility===
Amount of calves a female is able to have during her reproductive lifespan. 40% of elephants' population lives in wilderness and the fertility is not affected by stress therefore a wild female is able to have 10 calves, and semi-domesticated female is able to have 7 
=0.4*10+0.6*7
===Ratio of females in reproductive age===
Elephant female can have calves during her 15 to 50 years. 
=0.5714
===Ratio of females===
Ratio of females on elephants' population 
=53476
===Government regulation===
Index of government regulations <0;1>, 1 means no government regulation 
=1
===Mortality===
Ratio of dead elephants on the elephants' population. 
=((Population/Average lifespan) + Unnatural deaths)/Population
===Average lifespan===
=70
===Unnatural deaths===
Number of deaths that do not happen naturally 
=((Deaths by improper handling ratio*Population)+(Poaching ratio*Population))*Government regulations + Population*Deforestation ratio
===Deaths by improper handling ratio===
Ratio of deaths that happen due to unhuman behavior towards elephants and conditions they have to live in 
=0.01685
===Poaching ratio===
Ratio of deaths that happen because of elephants being hunted either for skin, tusks or to capture young calve 
=3.3e-05
===Deforestation ratio===
Ratio of deforastation in Thailand, this has a close correlation to number of elephants as this the major factor affecting the population 
=0.0035

=Results=
[[File:Thai elephant graph.PNG]]
[[File:Thai elephant table.PNG]]
 
As we can see, we can expect a continuous decrease in elephants' population in Thailand. By the year 2119 the elephants' population in Thailand should decrease by 2492 elephants.

=Conclusion=
In this simulation I created a functional model representing the evolution of elephants' population in Thailand. The results show continuous decrease over the course of following 100 years. However there is a room for improvements, like parameter deforestation ratio because nowadays the problem of deforestation is gaining on significance in general public eyes and this might lead into deforestation ratio decrease and potentially lead into elephants' population growth.

=Code=
[[File:Elephant population.mdl]]

=References=

File:Elephant population.mdl

2020-01-20T22:19:48Z

Xkavj12:

Indian Elephant Population in Thailand

2020-01-20T22:19:06Z

Xkavj12: /* Conclusion */

Indian Elephant Population in Thailand

2020-01-20T22:13:03Z

Xkavj12: /* Results */

File:Thai elephant table.PNG

2020-01-20T22:10:45Z

Xkavj12: Xkavj12 uploaded a new version of File:Thai elephant table.PNG

Indian Elephant Population in Thailand

2020-01-20T22:09:05Z

Xkavj12: /* Results */

Introduction

=Problem definition=
During the course of the 20th century, the population of indian elephants has decreased drastically, mostly due to a significant reduction of elephants' natural habitat, as well as decrease in utilization of elephants in logging industry and shift to a role of a tourist attraction.
This model showcases the evolution of elephants' population in Thailand for upcoming 100 years.

=Method=
The vensim modelling tool was selected for the purpose of this simulation.

=Model=
[[File:Thai_elepahnat_model.PNG]]
==Model variables==
===Population===
Number of elephants in Thailand. Starting value 8900. This is the variable that we are examining.
===Increase===
Number of elephants that are born 
=Natality*Population
===Decrease===
Number of elephants that have died 
=Mortality*Population
===Natality===
Ratio of newly born elephants to elephant population. Amount of newborn elephants equals fertility multiplied by number of females in reproductive age divided by 40*2 (number of reproductive years, multiplied by 2 as elephants pregnancy takes 22-24 months). We then multiply by Governement regualtion ratio. 
=((Fertility*((Ratio of females*Population)*Ratio of females in reproductive age)/80)*Government regulations)/Population
===Fertility===
Amount of calves a female is able to have during her reproductive lifespan. 40% of elephants' population lives in wilderness and the fertility is not affected by stress therefore a wild female is able to have 10 calves, and semi-domesticated female is able to have 7 
=0.4*10+0.6*7
===Ratio of females in reproductive age===
Elephant female can have calves during her 15 to 50 years. 
=0.5714
===Ratio of females===
Ratio of females on elephants' population 
=53476
===Government regulation===
Index of government regulations <0;1>, 1 means no government regulation 
=1
===Mortality===
Ratio of dead elephants on the elephants' population. 
=((Population/Average lifespan) + Unnatural deaths)/Population
===Average lifespan===
=70
===Unnatural deaths===
Number of deaths that do not happen naturally 
=((Deaths by improper handling ratio*Population)+(Poaching ratio*Population))*Government regulations + Population*Deforestation ratio
===Deaths by improper handling ratio===
Ratio of deaths that happen due to unhuman behavior towards elephants and conditions they have to live in 
=0.01685
===Poaching ratio===
Ratio of deaths that happen because of elephants being hunted either for skin, tusks or to capture young calve 
=3.3e-05
===Deforestation ratio===
Ratio of deforastation in Thailand, this has a close correlation to number of elephants as this the major factor affecting the population 
=0.0035

=Results=
[[File:Thai elephant graph.PNG]]
[[File:Thai elephant table.PNG]]
As we can see, we can expect a continous decrease in elephants' population in Thailand.

=Conclusion=

=Code=

=References=

Indian Elephant Population in Thailand

2020-01-20T22:05:32Z

Xkavj12:

Indian Elephant Population in Thailand

2020-01-20T22:05:01Z

Xkavj12: /* Results */

File:Thai elephant table.PNG

2020-01-20T22:04:12Z

Xkavj12:

File:Thai elephant graph.PNG

2020-01-20T22:03:57Z

Xkavj12:

Indian Elephant Population in Thailand

2020-01-20T21:57:49Z

Xkavj12: /* Model */

Indian Elephant Population in Thailand

2020-01-20T21:18:43Z

Xkavj12: /* Model */

File:Thai elepahnat model.PNG

2020-01-20T21:18:25Z

Xkavj12:

Indian Elephant Population in Thailand

2020-01-20T21:07:08Z

Xkavj12: /* Method */

Indian Elephant Population in Thailand

2020-01-20T21:04:27Z

Xkavj12: /* Problem definition */

Indian Elephant Population in Thailand

2020-01-20T17:42:42Z

Xkavj12: Created page with "Introduction =Problem definition= =Method= =Model= =Results= =Conclusion= =Code="

Introduction

=Problem definition=

=Method=

=Model=

=Results=

=Conclusion=

=Code=

WS 2019/2020

2020-01-20T17:42:18Z

Xkavj12:

Semestral papers from winter term 2019/2020. Please, put here links to the pages with your paper. First you need to have your [[Assignments WS 2019/2020|assignment approved]]

== Simulation ==
[http://www.simulace.info/index.php/Cotton_Processing_Quality:_Cotton,_Seed,_Lint,_Trash Cotton Processing Quality: Cotton, Seed, Lint, Trash] , Ibrahim Aghazada (in progress)

[http://www.simulace.info/index.php/Time_Series_Model_Building_Process Time Series Model Building Process] , Nikola Hažmuková (in progress)

[http://www.simulace.info/index.php/Indian_Elephant_Population_in_Thailand Indian Elephant Population in Thailand] , [[User:Xkavj12|Xkavj12]] ([[User talk:Xkavj12|talk]]) 18:42, 20 January 2020 (CET) (in progress)

== Textbook Chapters ==
[http://www.simulace.info/index.php/Limits_to_Growth Limits to Growth] , Ibrahim Aghazada (in progress)

Assignments WS 2019/2020

2019-12-22T16:56:25Z

Xkavj12: /* Simulation Proposal - Orders completion in a warehouse */

{{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|How to deal with the simulation assignment]].
</div>
}}

{{Ambox
| text = <div>
Topics on gambling, cards, etc. are not welcome.
</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>
}}

== Simulation Proposal - Shopping Centre Management ==

Each store in a shopping centre pays rent to the shopping centre landlord. Final rent that a store has to pay is calculated as a sum of fixed rent and percentage rent (based on a percentage of store sales). A company that manages shopping centres is profitable when all tenants of the centre are profitable. Sales among tenants are distributed by normal distribution with one outlier, which has double the sales of the second best. This tenant is typical for each shopping centre and is called an anchor tenant. Usually it is a hypermarket. The managing company has services costs, maintenance costs, marketing costs, which are distributed among the tenants in addition to rent. If a tenant can't afford to pay rent + costs, he will terminate lease and managing company loses profit from rent. Other variables affecting the profit are for example footfall of the centre (number of visitors), number of stores, size of the store, conversion ratio (ratio of people walking in to people buying something), average basket (average money spent per customer), anchor tenant sales ratio to all sales, average length of lease, percentage rent, risk of a tenant going out of business. Since getting sales data of each tenant in a shopping centre is not possible (confidential information), I will build the model with a reasonable deal of abstraction on freely available financial data and retail reports about shopping centers. I will study what percentage rent and fixed rent per square meter should the managing company employ to increase the probability of staying profitable in long term.

'''Title:''' Shopping Centre Management

'''Author:''' Dominik Tkáč, [[User:TKAD01|TKAD01]] ([[User talk:TKAD01|talk]]) 00:00, 13 December 2019 (CET)

'''Model type:''' Stock and flow diagram

'''Modeling tool:''' Vensim

[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:03, 13 December 2019 (CET) '''Approved.''' Make sure that you describe in detail in the report, how you have derived the equations from the available data.

== Simulation Proposal - Indian elephant population in Thailand ==

During my trip to Thailand I was very touched by a lecture on decrease in Indian elephant population in Thailand and their utilization in present mostly in tourism.
Indian elephant population has dramatically decreased over the course of 20th century mostly due to a change of a position of elephant
in human's life as well as significant reduction of their natural habitat. Based on available data of elephant's population,
natural and human threats and major influences on the elephant's numbers I want to find main factors affecting population of elephants in Thailand
as well as predict future population changes with increase in sustainable tourism.

'''Title:''' Orders completion in a warehouse

'''Author:''' Ján Káva [[User:Xkavj12|Xkavj12]] ([[User talk:Xkavj12|talk]]) 12:30, 11 December 2019 (CET) Edit: [[User:Xkavj12|Xkavj12]] ([[User talk:Xkavj12|talk]]) 17:55, 22 December 2019 (CET)

'''Model type:''' Stock and Flow Diagram

'''Modeling tool:''' Vensim

== Simulation Proposal – Cotton Processing Quality: Cotton, Seed, Lint, Trash ==

This simulation is inspired by previous experience as process management specialist in Cotton Processing Company in Azerbaijan. According to process, cotton was received from farmers and price was indicated based on the moisture and trash level of the raw material. Then raw cotton is going through individual steps of processing. Different types of products are being manufactured from the raw cotton with different qualities and prices.
The ''purpose of simulation'' is to analyze possible income of the company and create decision making threshold regarding acceptance and price of raw cotton received from farmers.

'''Title:''' Cotton Processing Quality: Cotton, Seed, Lint, Trash

'''Author:''' Ibrahim Aghazada

'''Model type:''' Stock and flow diagram

'''Modeling tool:''' Vensim

::[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 15:50, 15 December 2019 (CET) The idea is OK, just do not forget to make the simulation reasonably complex so that it would be useful in practice. Make sure that you describe in detail in the report, how you have derived the equations from the available data. '''Approved'''.

== Simulation Proposal - Atlantic Bluefin Tuna Population==

The population of tuna worldwide is decreasing due to being overfished. Yet some studies claim, that overfishing is not the main cause of the tuna population reduction. Christelle Ravier and Jean-Marc Fromentin in their paper "Long-term fluctuations in the eastern Atlantic and Mediterranean bluefin tuna population" came to the conclusion that the bluefin tuna population may be influence by biotic and environmental factors more than by overexploitation. This simulation will use available data of population size, juvenile death, environmental influences, fishing statistics and other to investigate whether overfishing is the main culprit for bluefin tuna population decline.

'''Title:''' Atlantic Bluefin Tuna Population

'''Author:''' Petra Vokálová, [[User:Vokp00|Vokp00]] ([[User talk:Vokp00|talk]]) 07:43, 9 December 2019 (CET)

'''Model type:''' Stock and flow diagram

'''Modeling tool:''' Vensim

:: [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:09, 11 December 2019 (CET) '''Approved'''. Make sure that you describe in detail in the report, how you have derived the equations from the available data (proving so that they are based on relevant data).

== Simulation Proposal - Population growth/decrease in EU in upcoming years==

This simulation aims to predict future development of population in EU. Concerns about the future of EU population have risen in recent years, since population gets older in first world countries and it does not make economical sense to have many children. Based on available statistical data about population growth, fertility decrease, immigration etc., this simulation should display trends of population growth or decrease, also in case of changes in certain variables, such as government actions (child support, better maternity leaves). Main source of data for this simulation will be Eurostat, an EU statists portal, I will also use "Demographic outlook for the European Union 2019", a European Parliament document.

'''Title:''' Population growth/decrease in EU in upcoming years

'''Author:''' Václav Pleskač, [[User:plev00|plev00]], 19 December 2019

'''Model type:''' Dynamic system

'''Modeling tool:''' Vensim

::[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 11:56, 20 December 2019 (CET) The idea is OK, just do not forget to make the simulation reasonably complex so that it would be useful in practice. Make sure that you describe in detail in the report, how you have derived the equations from the available data. '''Approved'''.

== Simulation Proposal - Crop Rotation in sustainable farming==

Crop rotation is based on growing a series of different types of crops in the same area in sequential seasons. The planned rotation may vary from a growing season to a few years or even longer periods. It is one of the most effective agricultural control strategies that is used in preventing the loss of soil fertility. It also helps in reducing soil erosion and increases crop yield. Planning an effective crop rotation requires weighing fixed and fluctuating production circumstances: market, farm size, labor supply, climate, soil type, growing practices, etc. In this simulation I will try to find parameters which have impact on the whole process of crop rotation with goal to find model providing desired outputs - high soil fertility, low soil erosion, good quality crops, high crop field and therefore higher revenue.

'''Title:''' Crop Rotation in sustainable farming

'''Author:''' Michal Šimánek, [[User:Simm04|Simm04]] ([[User talk:Simm04|talk]]) 20:33, 10 December 2019 (CET)

'''Model type:''' Stock and flow diagram

'''Modeling tool:''' Vensim

:: [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:13, 11 December 2019 (CET) What data will you build (derive the equations) your simulation on?

:: [[User:Simm04|Simm04]] ([[User talk:Simm04|talk]]) 20:02, 12 December 2019 (CET) I would use available dataset from https://www.nature.com/articles/s41598-017-14271-6#Sec16
::: [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:00, 12 December 2019 (CET) OK. '''Approved'''. Make sure that you describe in detail in the report, how you have derived the equations from the available data (proving so that they are based on relevant data).

== Simulation Proposal - Time Series Model Building Process==

Linear dynamic models, including univariate case Autoregressive Integrated Moving Average (ARIMA) models and multivariate case Vector AutoRegression (VAR) models, are mainstream approaches to modeling and forecasting time series in econometric practice. They are popular mainly for their simplicity. However, the model building process is not completely straightforward, and the practitioner has to make some decisions such as the transformation of time series or selecting a number of lags (orders p and q in ARIMA model). Recommendations for the decisions are usually formulated as 'cookbooks.' Since the different sources recommend different decision rules, the cookbooks may provide contradictory results. I propose to study decision rules for orders of autoregressive univariate models using MC simulation.
Specifically, I will create a set of data-generating processes, simulate the time series, build the models using the cookbooks, and compare the success rate of building a correct model. Based on the success rates of decision rules, I will compare the relative performance of different rules. Additionally, I will use different data-generating processes to study performance under varied assumptions. The choice rules will include General-To-Specific (GETS), specific-to-general, Schwarz-Bayesian Information Criterion (SBIC), and Akaike Information Criterion (AIC).

'''Title:''' Simulation Proposal – Time Series Model Building Process

'''Author:''' Nikola Hažmuková, [[User:Hazn00|Hazn00]] ([[User talk:Hazn00|talk]]) 18:59, 13 December 2019 (CET)

'''Model type:''' Monte Carlo

'''Modeling tool:''' Python

: This is on the edge of our scope, however sounds interesting, hence worth to try. Please, just bear in mind that the solution must be an original work for this course. If you would use any part done for any other occasion (another course, work, etc.), it is necessary to distinguish it clearly in your paper. '''Approved.''' [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 15:59, 14 December 2019 (CET)

Assignments WS 2019/2020

2019-12-14T21:08:50Z

Xkavj12: /* Simulation Proposal - Orders completion in a warehouse */

{{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|How to deal with the simulation assignment]].
</div>
}}

{{Ambox
| text = <div>
Topics on gambling, cards, etc. are not welcome.
</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>
}}

== Simulation Proposal - Shopping Centre Management ==

Each store in a shopping centre pays rent to the shopping centre landlord. Final rent that a store has to pay is calculated as a sum of fixed rent and percentage rent (based on a percentage of store sales). A company that manages shopping centres is profitable when all tenants of the centre are profitable. Sales among tenants are distributed by normal distribution with one outlier, which has double the sales of the second best. This tenant is typical for each shopping centre and is called an anchor tenant. Usually it is a hypermarket. The managing company has services costs, maintenance costs, marketing costs, which are distributed among the tenants in addition to rent. If a tenant can't afford to pay rent + costs, he will terminate lease and managing company loses profit from rent. Other variables affecting the profit are for example footfall of the centre (number of visitors), number of stores, size of the store, conversion ratio (ratio of people walking in to people buying something), average basket (average money spent per customer), anchor tenant sales ratio to all sales, average length of lease, percentage rent, risk of a tenant going out of business. Since getting sales data of each tenant in a shopping centre is not possible (confidential information), I will build the model with a reasonable deal of abstraction on freely available financial data and retail reports about shopping centers. I will study what percentage rent and fixed rent per square meter should the managing company employ to increase the probability of staying profitable in long term.

'''Title:''' Shopping Centre Management

'''Author:''' Dominik Tkáč, [[User:TKAD01|TKAD01]] ([[User talk:TKAD01|talk]]) 00:00, 13 December 2019 (CET)

'''Model type:''' Stock and flow diagram

'''Modeling tool:''' Vensim

[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:03, 13 December 2019 (CET) '''Approved.''' Make sure that you describe in detail in the report, how you have derived the equations from the available data.

== Simulation Proposal - Orders completion in a warehouse ==

We need to optimize number of warehouse workers and packaging stations in a warehouse with cca 20 000 different products stored. There are workers that work on picking the products for orders from stock positions and there is also one worker per packaging station assigned. Picking products for one regular order takes 15 minutes on average and for one B2B order takes 90 minutes on average. Packaging one regular order takes 2 minutes on average and B2B order takes 45 minutes on average. Ratio of regular to B2B orders is 25:1.
We want to find out optimal set up of number of workers and packaging stations.

'''Title:''' Orders completion in a warehouse

'''Author:''' Ján Káva [[User:Xkavj12|Xkavj12]] ([[User talk:Xkavj12|talk]]) 12:30, 11 December 2019 (CET)

'''Model type:''' Discrete event

'''Modeling tool:''' Simprocess

: For Simprocess, we require a simulation of a real company / problem. Where you get your data from? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 15:46, 14 December 2019 (CET)
: The proposal is based on a real warehouse located in Ostrava for which I provide IT services, I have access to warehouse ERP data as well as I can consult any estimations with logisitics specialists. [[User:Xkavj12|Xkavj12]] ([[User talk:Xkavj12|talk]]) 22:08, 14 December 2019 (CET)

== Simulation Proposal – Cotton Processing Quality: Cotton, Seed, Lint, Trash ==

This simulation is inspired by previous experience as process management specialist in Cotton Processing Company in Azerbaijan. According to process, cotton was received from farmers and price was indicated based on the moisture and trash level of the raw material. Then raw cotton is going through individual steps of processing. Different types of products are being manufactured from the raw cotton with different qualities and prices.
The ''purpose of simulation'' is to analyze possible income of the company and create decision making threshold regarding acceptance and price of raw cotton received from farmers.

'''Title:''' Cotton Processing Quality: Cotton, Seed, Lint, Trash

'''Author:''' Ibrahim Aghazada

'''Model type:''' Stock and flow diagram

'''Modeling tool:''' Vensim

== Simulation Proposal - Atlantic Bluefin Tuna Population==

The population of tuna worldwide is decreasing due to being overfished. Yet some studies claim, that overfishing is not the main cause of the tuna population reduction. Christelle Ravier and Jean-Marc Fromentin in their paper "Long-term fluctuations in the eastern Atlantic and Mediterranean bluefin tuna population" came to the conclusion that the bluefin tuna population may be influence by biotic and environmental factors more than by overexploitation. This simulation will use available data of population size, juvenile death, environmental influences, fishing statistics and other to investigate whether overfishing is the main culprit for bluefin tuna population decline.

'''Title:''' Atlantic Bluefin Tuna Population

'''Author:''' Petra Vokálová, [[User:Vokp00|Vokp00]] ([[User talk:Vokp00|talk]]) 07:43, 9 December 2019 (CET)

'''Model type:''' Stock and flow diagram

'''Modeling tool:''' Vensim

:: [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:09, 11 December 2019 (CET) '''Approved'''. Make sure that you describe in detail in the report, how you have derived the equations from the available data (proving so that they are based on relevant data).

== Simulation Proposal - Black Friday Walmart Simulation ==

Various items in Walmart store have different values for customers and therefore are sought out by more agents. Agents (customers) decide whether to try to get the item based on the number of people already on the way to the item and also based on distance from the item. Agents try to get as much value in items, pay for them and get out before the store closes.

'''Title:''' Black Friday Walmart Simulation

'''Author:''' VÁclav Pleskač, [[User:plev00|plev00]], 13 December 2019

'''Model type:''' Multi Agent

'''Modeling tool:''' Netlogo

: I don't understand the point of the simulation. What is it good for? How you verify it provides meaningul results? How do you measure the value of the product for a customer? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 15:50, 14 December 2019 (CET)

== Simulation Proposal - Crop Rotation in sustainable farming==

Crop rotation is based on growing a series of different types of crops in the same area in sequential seasons. The planned rotation may vary from a growing season to a few years or even longer periods. It is one of the most effective agricultural control strategies that is used in preventing the loss of soil fertility. It also helps in reducing soil erosion and increases crop yield. Planning an effective crop rotation requires weighing fixed and fluctuating production circumstances: market, farm size, labor supply, climate, soil type, growing practices, etc. In this simulation I will try to find parameters which have impact on the whole process of crop rotation with goal to find model providing desired outputs - high soil fertility, low soil erosion, good quality crops, high crop field and therefore higher revenue.

'''Title:''' Crop Rotation in sustainable farming

'''Author:''' Michal Šimánek, [[User:Simm04|Simm04]] ([[User talk:Simm04|talk]]) 20:33, 10 December 2019 (CET)

'''Model type:''' Stock and flow diagram

'''Modeling tool:''' Vensim

:: [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:13, 11 December 2019 (CET) What data will you build (derive the equations) your simulation on?

:: [[User:Simm04|Simm04]] ([[User talk:Simm04|talk]]) 20:02, 12 December 2019 (CET) I would use available dataset from https://www.nature.com/articles/s41598-017-14271-6#Sec16
::: [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:00, 12 December 2019 (CET) OK. '''Approved'''. Make sure that you describe in detail in the report, how you have derived the equations from the available data (proving so that they are based on relevant data).

== Simulation Proposal - Time Series Model Building Process==

Linear dynamic models, including univariate case Autoregressive Integrated Moving Average (ARIMA) models and multivariate case Vector AutoRegression (VAR) models, are mainstream approaches to modeling and forecasting time series in econometric practice. They are popular mainly for their simplicity. However, the model building process is not completely straightforward, and the practitioner has to make some decisions such as the transformation of time series or selecting a number of lags (orders p and q in ARIMA model). Recommendations for the decisions are usually formulated as 'cookbooks.' Since the different sources recommend different decision rules, the cookbooks may provide contradictory results. I propose to study decision rules for orders of autoregressive univariate models using MC simulation.
Specifically, I will create a set of data-generating processes, simulate the time series, build the models using the cookbooks, and compare the success rate of building a correct model. Based on the success rates of decision rules, I will compare the relative performance of different rules. Additionally, I will use different data-generating processes to study performance under varied assumptions. The choice rules will include General-To-Specific (GETS), specific-to-general, Schwarz-Bayesian Information Criterion (SBIC), and Akaike Information Criterion (AIC).

'''Title:''' Simulation Proposal – Time Series Model Building Process

'''Author:''' Nikola Hažmuková, [[User:Hazn00|Hazn00]] ([[User talk:Hazn00|talk]]) 18:59, 13 December 2019 (CET)

'''Model type:''' Monte Carlo

'''Modeling tool:''' Python

: This is on the edge of our scope, however sounds interesting, hence worth to try. Please, just bear in mind that the solution must be an original work for this course. If you would use any part done for any other occasion (another course, work, etc.), it is necessary to distinguish it clearly in your paper. '''Approved.''' [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 15:59, 14 December 2019 (CET)

Assignments WS 2019/2020

2019-12-13T20:30:45Z

Xkavj12: /* Simulation Proposal - Orders completion in a warehouse */

{{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|How to deal with the simulation assignment]].
</div>
}}

{{Ambox
| text = <div>
Topics on gambling, cards, etc. are not welcome.
</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>
}}

== Simulation Proposal - Shopping Centre Management ==

Each store in a shopping centre pays rent to the shopping centre landlord. Final rent that a store has to pay is calculated as a sum of fixed rent and percentage rent (based on a percentage of store sales). A company that manages shopping centres is profitable when all tenants of the centre are profitable. Sales among tenants are distributed by normal distribution with one outlier, which has double the sales of the second best. This tenant is typical for each shopping centre and is called an anchor tenant. Usually it is a hypermarket. The managing company has services costs, maintenance costs, marketing costs, which are distributed among the tenants in addition to rent. If a tenant can't afford to pay rent + costs, he will terminate lease and managing company loses profit from rent. Other variables affecting the profit are for example footfall of the centre (number of visitors), number of stores, size of the store, conversion ratio (ratio of people walking in to people buying something), average basket (average money spent per customer), anchor tenant sales ratio to all sales, average length of lease, percentage rent, risk of a tenant going out of business. Since getting sales data of each tenant in a shopping centre is not possible (confidential information), I will build the model with a reasonable deal of abstraction on freely available financial data and retail reports about shopping centers. I will study what percentage rent and fixed rent per square meter should the managing company employ to increase the probability of staying profitable in long term.

'''Title:''' Shopping Centre Management

'''Author:''' Dominik Tkáč, [[User:TKAD01|TKAD01]] ([[User talk:TKAD01|talk]]) 00:00, 13 December 2019 (CET)

'''Model type:''' Stock and flow diagram

'''Modeling tool:''' Vensim

== Simulation Proposal - Orders completion in a warehouse ==

We need to optimize number of warehouse workers and packaging stations in a warehouse with cca 20 000 different products stored. There are workers that work on picking the products for orders from stock positions and there is also one worker per packaging station assigned. Picking products for one regular order takes 15 minutes on average and for one B2B order takes 90 minutes on average. Packaging one regular order takes 2 minutes on average and B2B order takes 45 minutes on average. Ratio of regular to B2B orders is 25:1.
We want to find out optimal set up of number of workers and packaging stations.

'''Title:''' Orders completion in a warehouse

'''Author:''' Ján Káva [[User:Xkavj12|Xkavj12]] ([[User talk:Xkavj12|talk]]) 12:30, 11 December 2019 (CET)

'''Model type:''' Discrete event

'''Modeling tool:''' Simprocess

== Simulation Proposal - Santa Clause Elves & Scattered Gifts ==

This simulation is inspired by couple of animation movies from my childhood. Imagine, sleigh of the Santa crashed and all the gifts scattered. Elves try to move around and calculate all the gifts by moving to the sleigh. So, each elf moves randomly until he will found a gift, then he carries the gift to the sleigh. After he will put gift into sleigh he will perform operations again. The process will continue until all the gifts will be in sleigh.

'''Title:'''Santa Clause Elves & Scattered Gifts

'''Author:''' Ibrahim Aghazada

'''Model type:''' Multi Agent

'''Modeling tool:''' NetLogo

== Simulation Proposal - Atlantic Bluefin Tuna Population==

The population of tuna worldwide is decreasing due to being overfished. Yet some studies claim, that overfishing is not the main cause of the tuna population reduction. Christelle Ravier and Jean-Marc Fromentin in their paper "Long-term fluctuations in the eastern Atlantic and Mediterranean bluefin tuna population" came to the conclusion that the bluefin tuna population may be influence by biotic and environmental factors more than by overexploitation. This simulation will use available data of population size, juvenile death, environmental influences, fishing statistics and other to investigate whether overfishing is the main culprit for bluefin tuna population decline.

'''Title:''' Atlantic Bluefin Tuna Population

'''Author:''' Petra Vokálová, [[User:Vokp00|Vokp00]] ([[User talk:Vokp00|talk]]) 07:43, 9 December 2019 (CET)

'''Model type:''' Stock and flow diagram

'''Modeling tool:''' Vensim

:: [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:09, 11 December 2019 (CET) '''Approved'''. Make sure that you describe in detail in the report, how you have derived the equations from the available data (proving so that they are based on relevant data).

== Simulation Proposal - Black Friday Walmart Simulation ==

Various items in Walmart store have different values for customers and therefore are sought out by more agents. Agents (customers) decide whether to try to get the item based on the number of people already on the way to the item and also based on distance from the item. Agents try to get as much value in items, pay for them and get out before the store closes.

'''Title:''' Black Friday Walmart Simulation

'''Author:''' VÁclav Pleskač, [[User:plev00|plev00]], 13 December 2019

'''Model type:''' Multi Agent

'''Modeling tool:''' Netlogo

== Simulation Proposal - Crop Rotation in sustainable farming==

Crop rotation is based on growing a series of different types of crops in the same area in sequential seasons. The planned rotation may vary from a growing season to a few years or even longer periods. It is one of the most effective agricultural control strategies that is used in preventing the loss of soil fertility. It also helps in reducing soil erosion and increases crop yield. Planning an effective crop rotation requires weighing fixed and fluctuating production circumstances: market, farm size, labor supply, climate, soil type, growing practices, etc. In this simulation I will try to find parameters which have impact on the whole process of crop rotation with goal to find model providing desired outputs - high soil fertility, low soil erosion, good quality crops, high crop field and therefore higher revenue.

'''Title:''' Crop Rotation in sustainable farming

'''Author:''' Michal Šimánek, [[User:Simm04|Simm04]] ([[User talk:Simm04|talk]]) 20:33, 10 December 2019 (CET)

'''Model type:''' Stock and flow diagram

'''Modeling tool:''' Vensim

:: [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:13, 11 December 2019 (CET) What data will you build (derive the equations) your simulation on?

:: [[User:Simm04|Simm04]] ([[User talk:Simm04|talk]]) 20:02, 12 December 2019 (CET) I would use available dataset from https://www.nature.com/articles/s41598-017-14271-6#Sec16
::: [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:00, 12 December 2019 (CET) OK. '''Approved'''. Make sure that you describe in detail in the report, how you have derived the equations from the available data (proving so that they are based on relevant data).

== Simulation Proposal - Time Series Model Building Process==

Linear dynamic models, including univariate case Autoregressive Integrated Moving Average (ARIMA) models and multivariate case Vector AutoRegression (VAR) models, are mainstream approaches to modeling and forecasting time series in econometric practice. They are popular mainly for their simplicity. However, the model building process is not completely straightforward, and the practitioner has to make some decisions such as the transformation of time series or selecting a number of lags (orders p and q in ARIMA model). Recommendations for the decisions are usually formulated as 'cookbooks.' Since the different sources recommend different decision rules, the cookbooks may provide contradictory results. I propose to study decision rules for orders of autoregressive univariate models using MC simulation.
Specifically, I will create a set of data-generating processes, simulate the time series, build the models using the cookbooks, and compare the success rate of building a correct model. Based on the success rates of decision rules, I will compare the relative performance of different rules. Additionally, I will use different data-generating processes to study performance under varied assumptions. The choice rules will include General-To-Specific (GETS), specific-to-general, Schwarz-Bayesian Information Criterion (SBIC), and Akaike Information Criterion (AIC).

'''Title:''' Simulation Proposal – Time Series Model Building Process

'''Author:''' Nikola Hažmuková, [[User:Hazn00|Hazn00]] ([[User talk:Hazn00|talk]]) 18:59, 13 December 2019 (CET)

'''Model type:''' Monte Carlo

'''Modeling tool:''' Python

Assignments WS 2019/2020

2019-12-13T20:30:21Z

Xkavj12: /* Simulation Proposal - Orders completion in a warehouse */

{{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|How to deal with the simulation assignment]].
</div>
}}

{{Ambox
| text = <div>
Topics on gambling, cards, etc. are not welcome.
</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>
}}

== Simulation Proposal - Shopping Centre Management ==

Each store in a shopping centre pays rent to the shopping centre landlord. Final rent that a store has to pay is calculated as a sum of fixed rent and percentage rent (based on a percentage of store sales). A company that manages shopping centres is profitable when all tenants of the centre are profitable. Sales among tenants are distributed by normal distribution with one outlier, which has double the sales of the second best. This tenant is typical for each shopping centre and is called an anchor tenant. Usually it is a hypermarket. The managing company has services costs, maintenance costs, marketing costs, which are distributed among the tenants in addition to rent. If a tenant can't afford to pay rent + costs, he will terminate lease and managing company loses profit from rent. Other variables affecting the profit are for example footfall of the centre (number of visitors), number of stores, size of the store, conversion ratio (ratio of people walking in to people buying something), average basket (average money spent per customer), anchor tenant sales ratio to all sales, average length of lease, percentage rent, risk of a tenant going out of business. Since getting sales data of each tenant in a shopping centre is not possible (confidential information), I will build the model with a reasonable deal of abstraction on freely available financial data and retail reports about shopping centers. I will study what percentage rent and fixed rent per square meter should the managing company employ to increase the probability of staying profitable in long term.

'''Title:''' Shopping Centre Management

'''Author:''' Dominik Tkáč, [[User:TKAD01|TKAD01]] ([[User talk:TKAD01|talk]]) 00:00, 13 December 2019 (CET)

'''Model type:''' Stock and flow diagram

'''Modeling tool:''' Vensim

== Simulation Proposal - Orders completion in a warehouse ==

We need to optimize number of warehouse workers and packaging stations in a warehouse with cca 20 000 different products stored. There are workers that work on picking the products for orders from stock positions and there is also one worker per packaging station assigned. Picking products for one regular order takes 15 minutes on average and for one B2B order takes 90 minutes on average. Packaging one regular order takes 2 minutes on average and B2B order takes 45 minutes on average. Ratio of regular to B2B orders is 25:1.
We want to find out optimal set up of number of workers and packaging stations.

'''Title:''' Orders completion in a warehouse

'''Author:''' Ján Káva [[User:Xkavj12|Xkavj12]] ([[User talk:Xkavj12|talk]]) 21:30, 13 December 2019 (CET)

'''Model type:''' Discrete event

'''Modeling tool:''' Simprocess

== Simulation Proposal - Santa Clause Elves & Scattered Gifts ==

This simulation is inspired by couple of animation movies from my childhood. Imagine, sleigh of the Santa crashed and all the gifts scattered. Elves try to move around and calculate all the gifts by moving to the sleigh. So, each elf moves randomly until he will found a gift, then he carries the gift to the sleigh. After he will put gift into sleigh he will perform operations again. The process will continue until all the gifts will be in sleigh.

'''Title:'''Santa Clause Elves & Scattered Gifts

'''Author:''' Ibrahim Aghazada

'''Model type:''' Multi Agent

'''Modeling tool:''' NetLogo

== Simulation Proposal - Atlantic Bluefin Tuna Population==

The population of tuna worldwide is decreasing due to being overfished. Yet some studies claim, that overfishing is not the main cause of the tuna population reduction. Christelle Ravier and Jean-Marc Fromentin in their paper "Long-term fluctuations in the eastern Atlantic and Mediterranean bluefin tuna population" came to the conclusion that the bluefin tuna population may be influence by biotic and environmental factors more than by overexploitation. This simulation will use available data of population size, juvenile death, environmental influences, fishing statistics and other to investigate whether overfishing is the main culprit for bluefin tuna population decline.

'''Title:''' Atlantic Bluefin Tuna Population

'''Author:''' Petra Vokálová, [[User:Vokp00|Vokp00]] ([[User talk:Vokp00|talk]]) 07:43, 9 December 2019 (CET)

'''Model type:''' Stock and flow diagram

'''Modeling tool:''' Vensim

:: [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:09, 11 December 2019 (CET) '''Approved'''. Make sure that you describe in detail in the report, how you have derived the equations from the available data (proving so that they are based on relevant data).

== Simulation Proposal - Black Friday Walmart Simulation ==

Various items in Walmart store have different values for customers and therefore are sought out by more agents. Agents (customers) decide whether to try to get the item based on the number of people already on the way to the item and also based on distance from the item. Agents try to get as much value in items, pay for them and get out before the store closes.

'''Title:''' Black Friday Walmart Simulation

'''Author:''' VÁclav Pleskač, [[User:plev00|plev00]], 13 December 2019

'''Model type:''' Multi Agent

'''Modeling tool:''' Netlogo

== Simulation Proposal - Crop Rotation in sustainable farming==

Crop rotation is based on growing a series of different types of crops in the same area in sequential seasons. The planned rotation may vary from a growing season to a few years or even longer periods. It is one of the most effective agricultural control strategies that is used in preventing the loss of soil fertility. It also helps in reducing soil erosion and increases crop yield. Planning an effective crop rotation requires weighing fixed and fluctuating production circumstances: market, farm size, labor supply, climate, soil type, growing practices, etc. In this simulation I will try to find parameters which have impact on the whole process of crop rotation with goal to find model providing desired outputs - high soil fertility, low soil erosion, good quality crops, high crop field and therefore higher revenue.

'''Title:''' Crop Rotation in sustainable farming

'''Author:''' Michal Šimánek, [[User:Simm04|Simm04]] ([[User talk:Simm04|talk]]) 20:33, 10 December 2019 (CET)

'''Model type:''' Stock and flow diagram

'''Modeling tool:''' Vensim

:: [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:13, 11 December 2019 (CET) What data will you build (derive the equations) your simulation on?

:: [[User:Simm04|Simm04]] ([[User talk:Simm04|talk]]) 20:02, 12 December 2019 (CET) I would use available dataset from https://www.nature.com/articles/s41598-017-14271-6#Sec16
::: [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:00, 12 December 2019 (CET) OK. '''Approved'''. Make sure that you describe in detail in the report, how you have derived the equations from the available data (proving so that they are based on relevant data).

== Simulation Proposal - Time Series Model Building Process==

Linear dynamic models, including univariate case Autoregressive Integrated Moving Average (ARIMA) models and multivariate case Vector AutoRegression (VAR) models, are mainstream approaches to modeling and forecasting time series in econometric practice. They are popular mainly for their simplicity. However, the model building process is not completely straightforward, and the practitioner has to make some decisions such as the transformation of time series or selecting a number of lags (orders p and q in ARIMA model). Recommendations for the decisions are usually formulated as 'cookbooks.' Since the different sources recommend different decision rules, the cookbooks may provide contradictory results. I propose to study decision rules for orders of autoregressive univariate models using MC simulation.
Specifically, I will create a set of data-generating processes, simulate the time series, build the models using the cookbooks, and compare the success rate of building a correct model. Based on the success rates of decision rules, I will compare the relative performance of different rules. Additionally, I will use different data-generating processes to study performance under varied assumptions. The choice rules will include General-To-Specific (GETS), specific-to-general, Schwarz-Bayesian Information Criterion (SBIC), and Akaike Information Criterion (AIC).

'''Title:''' Simulation Proposal – Time Series Model Building Process

'''Author:''' Nikola Hažmuková, [[User:Hazn00|Hazn00]] ([[User talk:Hazn00|talk]]) 18:59, 13 December 2019 (CET)

'''Model type:''' Monte Carlo

'''Modeling tool:''' Python

Assignments WS 2019/2020

2019-12-12T10:27:31Z

Xkavj12: