Assignments WS 2020/2021
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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.
Topics on gambling, cards, etc. are not welcome.
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.
- 1 Spread of 19-COVID
- 2 NFL Free Agency
- 3 COVID-19 mass testing
- 4 Operation of private dental office
- 5 Widening the spread between rich and poor
- 6 Rhino population in Africa
- 7 Garbage collection
- 8 Financial budget of football club
- 9 IT Team simulation
- 10 COVID 19 symptoms
- 11 Investment decision maker
- 12 Lawn Mower Roboter
- 13 Retirement Planning
- 14 Covid 19 - Contract Tracing
- 15 Evolution of retirement pay in the Czech Republic
- 16 Castle Siege
- 17 Hunting Sharks Simulation
- 18 Risk Simulation in Banking
- 19 Effects of VAT exemption abolition to imported low value consignments
Spread of 19-COVID
Simulation : I will build a dynamic model of an epidemic his the dynamic issues. I will focus on the spread of Covid-19 in a population and Specially I will try to modelize the effect of a lockdown on the number of infections and deaths. I will start with a susceptible population, with one infected people that infect 10 people with a certain probability. When you are infected you go the doctors and with a certain probability you go in the recovery population or in the hospital. Then you have a percentage of chance to die in this hospital or to recover. The lockdown will triggered when the ratio of people who where to the doctor and total population exceed a certain percentage. We lockdown and by reducing the number of people you infect in the beginning.
Goal of simulation : I aim to model the impact of a lockdown on the spread of COVID on a population. It will also show the difference between countries, for example if we lockdown too late. What will be the impact of these decisions.
Method : I will use VensimPLE for this simulation, as it is a dynamic system, and In my home university I know that I will need to use VensimPLE for a future project and course so it will help me a lot.
- The topic souds good - the question is, on what data sources will you base your simulation (equations) on? Oleg.Svatos (talk) 22:13, 12 December 2020 (CET)
- I will use the case of Switzerland and use data from this website (https://corona-data.ch). I will try to reproduce the number of cases and the speed of the spread.Toscool (talk) 13:39, 13 December 2020 (CET)
- OK. Approved but do not forget to include in the report for the simulation how you have derived the equations in the simulation from the data. Oleg.Svatos (talk) 22:49, 14 December 2020 (CET)
- The topic souds good - the question is, on what data sources will you base your simulation (equations) on? Oleg.Svatos (talk) 22:13, 12 December 2020 (CET)
NFL Free Agency
Simulation : Free agency is a period during the off-season in the National Football League in the US. During that period, all 32 teams in the league can sign active players that have no contract with any other team, so-called free agents. The process goes as follows: at the beginning of free agency a certain amount of players become free agents due to expiring contracts. All players belong to one out of 8 position groups and want to receive a certain salary. Their starting position on the simulation grid is randomly assigned and they will move over the grid. The overall number of free agents is defined manually while they are randomly distributed over all position groups, as well as their desired salary, which is within a certain manually defined range. Whereas all the teams are looking for players from certain position groups and have a certain amount of money they can spend on them. The teams have fixed positions on the grid and do not move during the simulation. The maximum number of players a team is looking for is defined manually, while the desired position group is defined randomly from the list of position groups and the money to spend is randomly distributed over a certain manually defined salary range. When the simulation starts, the initial demand and supply ratio of a specific position is calculated and affects a player’s value. This means a player’s desired salary rises or decreases due to that demand and supply ratio. During the simulation players move over the grid. Players and teams get in touch when they are located next to each other. When a team’s position group needs matches the player’s position group and a player’s salary fits the money a team offers, the team signs this player and he disappears from the free agency market (turtle dies). If the offer doesn’t fit the need, a player walks on to the next team (turtle takes a random angle turn and walks until it approaches another team). Each team can negotiate only with one player at a time, and vice versa. With every round/tick/signing the demand and supply ratio is recalculated and the desired salary of all players in each position group changes and so does the amount of money teams are able to spend on further players (assuming they just signed a player). Free agency ends after a distinct number of ticks or even earlier if there are no more players left or teams do not have any money left to spend.
Goal of simulation : is to find out how a player’s value changes during the period of free agency. Especially interesting is, whether players that sign a new contract early in the period received higher payments or the ones signing late in the period. Maybe a certain strategy can be deducted for players depending on their initial demand and supply ratio in order to reach a highly paid contract.
Method : Since I don’t know VensimPLE yet, I think I will use NetLogo, because I see some similarities between my case and the “Market Structure” case we modelled recently.
- It is a bit unusual, but I can see something in common rather with Market Structure than with Building Escape. Please, just elaborate it into a greater detail and specify, how exactly should your simulation work. I am not sure you have a coherent idea about the solution. But if you work this out, I don't see a problem. Tomáš (talk) 21:45, 11 December 2020 (CET)
- Yeah you are right I meant the Market Structure, sorry for the confusion! Okay, I updated the description above trying to go more into details. TimWalenczak (talk) 14:14, 18 December 2020 (CET)
COVID-19 mass testing
Simulation : I will create simulation for mass Covid-19 testing in Slovakian village or small city. In previous rounds of this real mass testing in Slovakia testing itself took place in one day and in one sampling point, this will be the same with this simulation. In this model roles (medical staff, administrative workers, and police officer), will have assigned costs to them in order to include financial aspect into the simulation. Duration of the simulation will be 4 hours. This will serve as base model which will be adjusted in two ways. Firstly, I will create another model in which I will duplicate sampling point so 2 sampling points will be in simulation. Second adjustment to the base model will be that simulation time will be prolongated to 8 hours. After running all 3 models, outputs will be compared and the optimal one will be selected.
Goal of simulation : In the previous rounds of COVID-19 mass testing in Slovakia certain sampling points had experienced massive overload and were not prepared for the amount of citizens incoming to be tested. Therefore, this simulation would aim to simulate the scenario with data from previous testing rounds and might be helpful if the governments decides to repeat mass testing again.
Method : Discrete simulation - SIMPROCESS
- The topic looks generaly good, my only concern is that is could be too simple. What steps of the model do you plan? Where do you obtain the real data? Tomáš (talk) 02:54, 17 December 2020 (CET)
- I plan to obtain data from this site https://www.svidnik.sk/oznamy/druhe-kolo-plosneho-testovania-vysledky.html - on this website number of patients to be tested and number of points/places that take samples can be found. I know that each point/place has to have: 1 healthcare worker, 2 administrative workers and 1 police officer. Data about hourly rate can be obtained from this site: https://www.platy.sk/platy. Maybe I would like to adjust my original proposal, there would not be 1 point/place taking samples but 9 and I would create another simulation for more or less points/places. Generally I like the idea of splitting patients into two groups and I might include that in my simulation as well. One would consist of people older than 60 and the other one would consist of the rest of population. I will split the population according to demographic structure of Slovakia https://sk.wikipedia.org/wiki/Demografia_Slovenska#Vekov%C3%A1_%C5%A1trukt%C3%BAra. Steps I can think of right now: Patients entering, splitting the patients, administrative work, waiting, taking samples, waiting, receiving results, again splitting patients based on the results (negative ones can go home with certificate and positive ones would require additional steps like receiving information what to do next etc.) and the the simulation would end. Milan P (talk) 00:05, 18 December 2020 (CET)
Operation of private dental office
Author : Dufa00 10:50, 19 December 2020 (CET)
Simulation : I would simulate data and conditions of a real private dental office situated in central Bohemia. The Simulation will consist of the aspects influencing the company operations from within and from the outside. Nowadays even the COVID-19 is influencing the revenues and it would be interesting to see how it affects the company.
Goal of simulation : To help the specific dental office to react on possible dangers and see the hidden opportunities that might be available once the simulation is done. Whatsmore the results should be appliable to any other average private dental office.
Method : VensimPLE
about nanorobots vs. cancer: An interesting idea. Unfortunately, because this is completely unrealistic, you cannot work with any reasonable data and it means that you are not able to prove the meaningfulness of the results. Please suggest something else. Tomáš (talk) 03:04, 17 December 2020 (CET)
update: I see, I was thinking that this might happen, is the new proposal better? Dufa00 11:03, 19. December 2020 (CET)
Widening the spread between rich and poor
Author : Sára 21:00, 14 December 2020 (CET)
Simulation : After 2007-9 world economic crisis a new monetary policy, rather unconventional, was established to escape recessions/depressions. It is called quantitative easing. Although this tool succeeded in reverting the depression and proved helpful during coming years, it is highly discussed what side effects this tool has. A lot of researches suggest that it widens the gap between rich and poor people and make prices of bonds and stocks highly overheated.
Goal of simulation : Based on macroeconomics theory and semantic experiences from quantitative easing and its influence on other macroeconomic agents like interest rate, inflation, monetary supply etc., i would like to simulate behavior of banks and people during quantitative easing and i would like to work with different values of macroeconomic agents and bank and people behavior in order to try to find out whether widening the spread between rich and poor is an unevitable effect, whether it is sustainable in long term and whether they are possibilities how to erase this side effect.
Method : NetLogo
- I like the topic (although quantitative easing is just an eufemism for money printing, hence the implications are quite predictable). Before I finally approve, please elaborate it deeper. How exactly you will simulate, what will be the agents, what will they do, etc. Tomáš (talk) 02:47, 17 December 2020 (CET)
- Agents will be banks and people, until now quantitative easing is been applied always in the situation when interest rates were low for example, it makes people more willing to borrow but banks less willing to lend so idea behind my research is to simulate the process of quantitative easing under different circumstances than it is normally. According to different circumstances i will change people's and banks's behaviors according to macroeconomics theory and empirical knowledge. Is that deep enough? Sára (talk) 21:01, 18 December 2020 (CET)
- I am afraid, it is not. What different circumstances would you test? Remind the level of detail of the assignments for our agent-based simulations. It should be quite clear what and how you will simulate. I am still not sure.
- BTW, quantitative easing is being used while low interest rates, because central banks have no other instrument to use. If the IR were high, it would typically be simpler to decrease it. Tomáš (talk) 20:03, 19 December 2020 (CET)
Rhino population in Africa
Simulation : Rhinos once roamed many places in Europe, Asia, and Africa. At the beginning of the 20th century, about 500 000 rhinos roamed Africa and Asia. By 1970, rhino numbers dropped to 70,000, and today, around 27,000 rhinos remain in the wild. Africa's rhino population could face extinction within 10 years, animal welfare experts have warned. South Africa has the largest population of the species in the world however, the species still remains under threat from poaching for its horn and from habitat loss and degradation. Data: http://www.rhinoresourcecenter.com/pdf_files/119/1192816187.pdf, http://www.scielo.org.za/pdf/koedoe/v59n1/15.pdf, https://rhinos.org/about-rhinos/rhino-species/black-rhino/
Goal of simulation : Based on the available data, I would like to simulate future development of the rhino population (probably the black ones in Africa, cause its most documented). The population is threatened by poaching and the loss of the natural environment. The shrinking population increases people's efforts to protect it from poachers but increases the demand for rhino horns.
Method : VensimPLE / Insight Maker
Simulation : My aim is to simulate garbage collection in a city from the city counciler's point of view. I will focus on 3 main standpoints, specifically Waste production, Waste collection and Waste processing. The amount of produced waste is dependent on the population of the city and the rate of waste production of 1 person per day. Waste collection will be dependent on the amount of garbage trucks and their capacity. The number of employees (drivers and garbage collectors) will also play a role in how many trucks per day can be deployed. The final standpoint, Waste processing, consists of waste incineration and recycling. Incineration and recycling facilities can process different amount of waste per day. The scope of simulation can be either in weeks or months.
Goal of simulation : Finding balance between the amount of produced waste and its disposal by regulating the number of employees, trucks, their capacity, and the number of facilities which can either incinerate or recycle waste depending on the type of waste. The population of the city and the waste production of 1 person will be also adjustable.
Method : VensimPLE
Upon further reevaluation I propose to make the model simpler by crossing out the Waste collection standpoint, so there will be Waste production and Waste processing left. On these standpoints I found a valuable source of data: https://www.mzp.cz/cz/odpady_podrubrika . Also, thanks to the available data from 2009 to 2019 I could model the probable evolvement of waste production and waste processing either in Prague or the Czech republic. Dobj02 (talk) 23:58, 18 December 2020 (CET)
Financial budget of football club
The purpose of this simulation is to simulate important financial aspects of the football club. How much sponsors, players, transfers of players, money for tickets, number of sold club´s souvenir influence the budget of the clubs.
Goal of simulation :
Finding a balance between incomes and expenses, so the football club could work without any money donation from owner of the club.
Method : VensimPLE
- I would take data from football club Slavia Prague, which announce almost all data for publicity. What it be possible to do it like that?
- From the public data you cannot get know-how how a football club works on inside and therefore you cannot build complete system model with its feedback loops. If you would map only the financial flows, the system dynamics is no good for that and the result would be some kind of calcualtion, but not a simulation. I would suggest to try something else.Oleg.Svatos (talk) 19:27, 18 December 2020 (CET)
IT Team simulation
I would like to create a simulation, which is based on a Process Diagram and which would describe the process of solving business requirements within the IT team in which I now work. The simulation would show the entire course of the process from the origin of the request to the passage of all phases To Develop - Code review - Testing - Acceptance - UAT - Done.
By simulation, I would deal with limited resources and limited specialization in the team. The goal would be to find out how many requests and in what rhythm our team would be able to deliver. As for the data basement - It would be based on the situation for the last two months. We solve projects in Jira and so I would be able to calculate how long the request lasted and when it returned to the previous stages + some average morbidity of team members, etc.
Method: SimProcess simulation
COVID 19 symptoms
The model will represent COVID 19. The nodes in the model will represent the common symptoms of COVID 19. According to the World Health Organisation (WHO, 2020) there are 8 common symptoms: fever, dry cough, fatigue, shortness of breath, loss of appetite, confusion, persistent pain or pressure in the chest, high temperature (above 38 °C). The symptoms of said disease are thought to have direct causal relations with one another. If a person develops a symptom of COVID 19 (e.g. shortness of breath), this increases the likelihood of them developing other symptoms (e.g. loss of appetite, fever). Similarly, if one symptom disappears, the others might as well. The greatest danger is present for people vulnerable to the disease. The model will predict whether a person is vulnerable (due to high age) or resistant to the disease and take this in consideration.
Goal of simulation :
Each tick the probability of a symptom being developed will be calculated. The probability will depend on certain parameters + the total activation of the neighbouring symptoms at the previous tick. These parameters will be the supposed connection between the nodes (slider), influences unrelated to the disease (slider; said age or other respiratory diseases) and the threshold of each symptom.
Method : NetLogo
Investment decision maker
Author : mico00 18:13, 18 December 2020 (CET)
Simulation : the user has a limited amount of income, and can put in is certain funds. using monte-Carlo simulation, I'd like the user to be able to spread his funds to certain portfolios. these are prone to different oscillations and behavior throughout time. this becomes essentially a game, where the user has the power to work with his money, with the goal to maximize his profits after 10 year period. each transaction is punished by a certain amount of money for time costs.
Goal of simulation : Main goal is to learn how to handle money in an environment of uncertainty
Method : google sheets (essentially excel)
- This is too general. There were some simulations like that in the past, just look for them in previous years. For this kind of task you have to specify what precisely you will simulate, where you will get the data for it (you will derive the probability distributions from), and what new features does your simulation brings compared to the assignments done in the past at this course. The good real data are a must for the MonteCarlo simulation. Oleg.Svatos (talk) 19:36, 18 December 2020 (CET)
Lawn Mower Roboter
Simulation : The Simulation will show the movement and efficiency of a lawn mower robot in different environments (gardens) with different obstacles. It will take attributes like frequency of lawing, wished height of grass, duration of lawing and the power consumption into account. Different algorithms for the movement and the treatment of obstacles will be tried. The limit for the lawing could be a wished height with a defined deviation which is not allowed to be exceeded. The data for the power consumption and duration of lawing can be extracted from variuos providers.
Goal of simulation : Optimize the lawing frequency and selected lawing height, so that the power consumption is the lowest and the deviation of the wished height of the grass is not exceeded.
Method : NETLogo
Simulation : Investing in shares can contribute a great deal to old-age provision. Therefore, I would like to simulate the portfolio decision of a young family. They already have a portfolio of shares and plan to continue investing a fixed amount each year. The decision is to continue to invest in a fixed stock index (SP500) or to invest in a portfolio of 4 CTX stocks from now on.
Data Source: Yahoo Finance
Goal of simulation : The aim of the simulation is to compare the two portfolios and calculate their probable value in 30 years and what interest income the family can expect in 30 years.
Method : Excel / Monte Carlo
Covid 19 - Contract Tracing
Simulation : The Covid 19 global pandemic has an impact on all our lives. Especially the lockdowns in all countries - including the Czech Republic and Germany. The main goal of these lockdowns is to reduce the number of contacts so that contacts of infected people can be traced and chains of infection can be broken. In my simulation, I would like to show the impact of higher distances between people and the prohibition of large public events on the number of infected people. Contacts with infected people are represented by links, infections are shown by recoloring of the agent. The simulation will show the effects when wearing masks and when not.By this the simulation shows the effect in reducing infections by keeping distance, banning mass events and wearing masks.
Data Source: Data on infection incidence sufficiently available - use only scientific sources
Goal of simulation : Showing the importance of keeping distance and holding onto rules in a global pandemic, to show the impact everbody has in these times.
Method : Netlogo
Evolution of retirement pay in the Czech Republic
Simulation : Nowadays a lot of people say that the Czech Republic will have problems with the retirement pay in the future. So, I decided to create a simulation, which will show a prediction of average retirement pay in the Czech Republic for next 50 years. The average retirement pay depends on more factors and I decided to predict it depending on GDP, state debt, population, mortality and natality.
Data Source: I will use data from mfcr.cz and czso.cz
Goal of simulation : The aim of the simulation is to predict the evolution of average retirement pay in the Czech Republic and to find out how much money people will get in the future.
Method : VensimPLE
Simulation : The simulation includes field area and the castle area, attacker agents will have to cross the field area which has an adjustable number of barricades and reach the gate in the castle area then sufficiently damage it to break it. Defender agents will shoot arrows from the castle walls to hinder attackers' progress and protect the gate and subsequently the castle. Attackers and defenders will have multiple types.
Data Source: Number of attackers and defenders and value of their attributes will be adjustable by a common user.
Goal of simulation : Allowing user to generate custom scenarios and saving their results.
Method : Netlogo
Hunting Sharks Simulation
Simulation : I would like to create a simulation of life in the ocean, specifically shark hunts. In the simulation, there will be two types of agents, fish forming a shoal and sharks in an adjustable number. The first step will be to implement a swarm / shoal movement algorithm for fish agents. The fish will try to avoid the sharks, although they will be slower, but much more mobile in changes of direction. They will also randomly spawn and die. Sharks will have two modes controlled by hunger. If the shark is full, it will just roam the ocean. If the shark is hungry, it switches to hunting mode. This is where the fun begins. The shark speeds up and starts hunting. When moving in one direction, its speed may increase even more. A shark in hunting mode will also have a greater vision range than fish. If there are more sharks, it would be possible to implement reproduction or more types of food for shark (some can be more attractive for them).
Data Source: Data traceable on the Internet, such as the swimming speed of sharks and common fish.
Goal of simulation : We do know that sharks are solitary animals, for the most part of live. They typically live and hunt by themselves, joining up with other sharks only in certain circumstances, such as mating. I would like to answer the question of whether it would be beneficial for sharks to form "packs".
Method : NetLogo
Risk Simulation in Banking
Simulation: Since the Financial Crisis 2007/08 the systematic relevance of banks came into public focus. Excessive risk taking together with an interdependent banking sector led to a dangerous snowball effect which in most countries could only be fixed by massive bail-outs programs. The exchange of liquidity in between commercial banks on the interbank market, while being beneficial in normal times, offers a treat to the systems stability during black swan events. I therefore plan to simulate the banking market in an arbitrary country and test its resilience to said events with different grades of safety mechanisms (like the Basel III rules for Capital requirements, leverage ratio and Liquidity requirements) in place.
Goal of Simulation: The goal of the Simulation is to access the effectiveness of different measures that were introduced to bolster the financial systems stability. At the same time, I will try to fit the simulation parameters to those of the actual german banking market and try to derive the probabilities of a systematic collapse.
Data source: Deutsche Bundesbank, ECB
Method: Since the non-spatial nature of this topic, I think a MC-Simulation is the best method here.
- The input-parameters would be balance sheet information from the banks like leverage-ratio, liquidity or total assets (possibly with a projection over future years). Variables would be the default probabilities of other banks/private customers. Also I think about including certain "black swan" events like the bursting of housing bubbles or corona. Simon (talk) 14:17, 19 December 2020 (CET)
Effects of VAT exemption abolition to imported low value consignments
Simulation: From 1. 7. 2021 EU Customs Codex has abolished the VAT (Value added tax) exemption limit on imported low-value goods (consignments below 22€). This means, that even for such small consignments, the VAT from the imported goods will have to paid in the state of the consumption. The goods below 150€ will still be exempt from standard customs duties, unless the goods are subject to eg. excise or such. The point of my simulation will be to estimate the novel impacts to the foreign trade (mainly import regimes) volume of the Union.
Goal of Simulation: There are two goals of this simulation. Firstly, to determine the effects of the novel introduction to the tax revenue in the Czech Republic. Secondly, the simulation should be also able to estimate, if this novel will have any impact on the foreign trade in general - can we expect a decrease, or will it not affect the amount of imported goods?
Data source: Intrastat, ČSÚ
Method: Monte Carlo simulation