Assignments WS 2021/2022
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Contents
Spread of covid19 in closed/open area markets
In winter 2021 in Czechia the christmas markets were banned due to another covid19 infection wave. On the other hand people are free to go into shopping malls. It would be interesting to use existing data about covid19 virus transmission in agent based simulation to see how many people get infected and in what speed depending on whether they are in a christmas (open) market, or in a shopping mall (closed). The main goal will be to see if the simulation would backup the decision that has been made about christmas markets.
Possible research papers that contain data about covid spreading
- Kaggle notebook - Covid19, Evolution, Transmission, Spatial Patterns
- Research - Understanding COVID-19 transmission, health impacts and mitigation: timely social distancing is the key
This simulation would be realised using NetLogo.
Summary:
WHAT will be simulated
- market place, which can be both open space or closed space.
- people with or without masks, who will walk from shop to shop, with some intention and some of them will be virus carriers
- virus, which will spread in places where people go through (depending on the closed/open area, the infection rates will differ)
GOAL of the simulation
- answer the question: "Where is the virus spread more significant? At the market place, or at the shopping mall?"
TOOL used for the simulation
- NetLogo
- Agent based simulation
Author: Angel Kostov, xkosa20
Effects of COVID-19 vaccination on the spread of infection
Simulation
Currently there is a new wave of the COVID-19 pandemic. Although a certain percentage of the population has already been vaccinated, this is obviously not enough to prevent further COVID-19 measures.
The purpose of the simulation is to show how COVID-19 vaccination affects the spread of the pandemic. I will use an agent-based model in order to simulate the scenario in a simplified form based on existing scientific data. In addition, current COVID-19 measures are considered.
Subjects of the simulation:
Environment:
- A village with around 6.000 inhabitants
- Simplified: The village is closed that is new people cannot come in and people of the village cannot go out
Agents:
- Vaccinated persons
- Unvaccinated persons
- Simulations with different vaccination rates to compare the different infection courses
Further measures:
- All people wear masks
- Nobody wears a mask
Start:
- Few agents are unknowingly infected (e.g. 0,1% of the inhabitants = 6 people)
- Movement of agents intended to reflect the daily behavior of people in real life in a simplified form.
- One agent can infect another agent with a certain probability if they are close to each other.
- The probability of an infection depends on the measure (vaccination / mask)
Goal:
- Identify the infection course with different vaccination rates and measures.
- Showing the importance of vaccination.
Method
- NetLogo
Possible data sources
https://www.rki.de/SharedDocs/FAQ/COVID-Impfen/FAQ_Liste_Wirksamkeit.html
Chia, P. Y., Xiang Ong, S. W., Chiew, C. J., Ang, L. W., Chavatte, J.-M., Mak, T.-M., Cui, L., Kalimuddin, S., Chia, W. N., Tan, C. W., Ann Chai, L. Y., Tan, S. Y., Zheng, S., Pin Lin, R. T., Wang, L., Leo, Y.-S., Lee, V. J., Lye, D. C., & Young, B. E. (2021). Virological and serological kinetics of SARS-CoV-2 Delta variant vaccine-breakthrough infections: A multi-center cohort study. Clinical Microbiology and Infection, S1198743X21006388. https://doi.org/10.1016/j.cmi.2021.11.010
Eyre, D. W., Taylor, D., Purver, M., Chapman, D., Fowler, T., Pouwels, K., Walker, A. S., & Peto, T. E. (2021). The impact of SARS-CoV-2 vaccination on Alpha and Delta variant transmission [Preprint]. Infectious Diseases (except HIV/AIDS). https://doi.org/10.1101/2021.09.28.21264260
Harder, T., Külper-Schiek, W., Reda, S., Treskova-Schwarzbach, M., Koch, J., Vygen-Bonnet, S., & Wichmann, O. (2021). Effectiveness of COVID-19 vaccines against SARS-CoV-2 infection with the Delta (B.1.617.2) variant: Second interim results of a living systematic review and meta-analysis, 1 January to 25 August 2021. Eurosurveillance, 26(41). https://doi.org/10.2807/1560-7917.ES.2021.26.41.2100920
Author: Laura Kundmueller
- OK, but, please, elaborate it a bit. How exactly should the simulation look like, kinds of agents, etc. And mainly: the sources of data, etc. Tomáš (talk) 12:00, 10 December 2021 (CET)
Simulation of genetic algorithm: Travelling Salesman Problem
Simulation
The topic of this simulation is an old graph problem, Travelling Salesman Problem. My approach would be based on genetic learning algorithm. A random map will be generated at the start. Salesman is travelling in a car with some gas. The gas is used as he travels, it can be recharged at gas stations but it costs money. The map contains some hills and flat roads, which have a different cost of gas when going through.
The goal is:
- to find the optimum path between the towns.
The parameters are:
- number of agents (travelling salesmen)
- gas in car
- money
- number of towns
- number of hills
- number of gas stations
Method
- NetLogo
Author: Mart13 (talk) 09:57, 9 December 2021 (CET)
- Although this isn't a true agent-based simulation, we sometimes accept topics from artificial intelligence and other related fields. However, it is necessary to elaborate it in deep. How exactly the algorithm will work. What is the goal (not the goal of the agent, but the goal of this work)? Etc. Tomáš (talk) 12:03, 10 December 2021 (CET)
Optimizing the process of baking wedding sweets
Simulation There is a wedding tradition in Czech Republic of baking wedding sweets and then handing them out to the guests of the weeding as a form of invitation. Process of baking usually takes whole day and several helpers in the kitchen are needed. Into paper baskets are usually packaged two types of sweets: several small ones with 3 different flavours and one so-called "rohový koláč". Which are then delivered by the bride to wedding guests. For the purpose of this simulation are process and needed ingredients simplified.
The goal is: The goal is to optimize the number of helpers in the kitchen and find optimal amount of basic ingredients for specified number of guests.
Method: Discrete simulation - SIMPROCESS
Entities:
- sweets
- paper baskets
- baking trays
Resources
- pastry-cooks
- bride
- flour
- sugar
- curd
- plum jam
- poppy seed filling
Process steps
- order for paper basket
- preparing sweets: small ones (3 different flavours), "rohove kolače" sweets (using all flavours)
- baking in the oven
- sugar coating
- packaging
- delivery
Data:
- https://www.svetsvateb.cz/2021/02/623262-svatebni-kolacky/
- https://megvkuchyni.cz/recepty/speciality/svatebni-special-jak-na-svatebni-kolacky/
- experience
Author: Michaela Červinková (cerm18) (talk) 10:16, 8 December 2021 (CET)
Carsharing company fleet optimization
Problem definition
Recently, carsharing becomes more and more popular in large cities. Short-term rental (from several minutes to 24 hours) of a car with possibility to drop it anywhere in the allowed area in the city attracts people who for some reasons do not want to use their own vehicles. However, it is not always convenient. If the fleet is relatively small, the probability that a car will be somewhere close by is also quite low. Cars also must be refueled or recharged sometimes by external staff, which would increase cost of the fleet maintenance with increasing of the fleet size.
Simulation
The proposing agent-based simulation will reproduce real situation with shared cars. Two types of agents are planned:
- cars with different states (waiting, in rent, maintenance) and characteristics (mileage, fuel level)
- drivers - users of the service, who rent the cars and have their own behavior, including decision making on taking a car, driving style, and so on.
Some data for the model will be obtained as personal observations of two carsharing services operating in Prague, Anytime and Uniqway (for example, number of available cars, which is visible in mobile applications). Another source of data would be statistics collected by other services abroad, for example, by operating in Russia service Yandex.Drive[1].
The goal is: to find out optimal fleet size and structure and price policy to maximize revenue of a carsharing company.
Method: agent-based simulation - NetLogo
Author: Sergei Shcherbinin (shcs00) (talk) 12:34, 8 December 2021 (CET)
