Difference between revisions of "Assignments WS 2016/2017"
|Line 19:||Line 19:|
Revision as of 10:52, 13 December 2016
Please, put here your assignments. Do not forget to sign them. You can use ~~~~ (four tildas) for an automatic signature. Use Show preview in order to check the result before your final sumbition.
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.
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.
Brownian motion Stock simulation (Willem Van de Velde, wilv00)
The simulation will contain the evolution of a portfolio of stocks. Each stock has a certain drift, volatility and initial market price. Over time the value of a stock change dependent on a brownian motion and the time. A person wants to invest a certain amount of money in stocks.
The goal of this simulation is to see how the persons initial investment will evolve over time, what portfolio structure would be ideal for the initial investment?
Method: Monte carlo Simulation; Program: Excel
Simulation proposal (Jakub Esterka, xestj00)
Simulation (in NETLOGO) will be set up as a FPS computer game (e.g. Counter Strike) with two teams and set number of players in each team (between 1 and 64). Goal of a simulation will be to find out how much more members can other team have for winning rate to be still 50 % in average. Second goal will be to find out how big advantage randomly selected player has to have for his team to dominate (after 10 games). And the third goal is to find the average rate of domination – how many games is needed for one team to start to dominate the other in every game (team members have almost maximum accuracy of 100).
- Each team can have 1 – 10 players
- Each team begins opposite of each other
- Each player moves randomly and have random accuracy (1-20)
- One player from each team can have an advantage (accuracy of 80)
- When two players from opposite teams meet, they shoot at each other with random accuracy
- If one player shoots the other one, he has its shooting accuracy increased
- When all players from one team die, game resets but players keep their accuracy (except for the first goal)
First goal is obligatory and in this research players will not keep their accuracy. If the simulation will work as planned and it will be possible for players to keep their accuracy, other goals are viable as well.
Software Developers (xvatj00)
There is a small company for software development. The company takes small orders (around 3 months long) for software. The software development process consists of 3 parts - analysis, coding and testing. For each project, there is a set number of analysts, programmers and testers, who work on the given project (and no other) until it’s finished. There are 2 main types of orders - well defined and very generally defined. For well defined orders (30% of all orders), the average time of the process of analysis is shorter than in case of the generally defined order, and requires less analysts. The company knows the average times of all parts of the development as well as the average salaries of the three positions. Each part of the development also has its probability of delay and average delay (in case delay occurs). There are different scenarios in cases of delays. Alongside specific positions, there are also “ultimate” workers, who work on the project from its beginning until the end - meaning they do all 3 parts of the development themselves. These workers have higher salaries (all are seniors), but take less time to finish the work. Method: Simprocess
Goal of the Simulation
The goal is to see, if it’s more convenient to have specialized workers, or to hire “ultimate” workers instead, and to have an overview of the projects’ employee expenses. To reach the goal, the plan is to create 1 simulation which takes into consideration only the process with the positions divided, and a second simulation which shows the process of “ultimate” workers. In both cases, the process will be taking all the incoming orders - there will be only this one type of process.
Police System (Kateryna Ushanova, xushk00)
This simulation will show police system and how this system will impact the crime rate of the city. Criminals will try to destroy the city's infrostructre and to make crime against civilians. In this simulation I will use three strategies that maybe used to fight crime:
1) applying medium-sized police force
2) a strategy in which a small police force attempt to recruit civilians into the police force
3) the police react on the crime in a brief period of time
The most important factor that influence skill of the police to fight the crime is work experience. The amount of experience is propotional to the cost of fighting crime.
The criminals will be walking randomly around the visual area. During their walking there is a random chance that they will commit a crime. When they do the crime, the civilians around them become victims, and the area they occupy becomes a bad zone. Bad zone make people more likely to turn to crime. Two main factors influence whether or not civilians will turn to crime:
1)the level of the city (user controls)
2)the simulated factors (the result of the police work; the state of the zone; the effects of random events that the user controls)
The goal of this simulation is:
- to see how changing the work experience level effects each strategy.
- to test out different strategies and factors to see how this effects the crime rate.
- to observe possible outcomes by changing techniques and factors in a different ways.
Method - NetLogo
(Poison and Insect Population, Kellianne Stefl)
NetLogo simulation of the steady decline in insect population in Germany from 1989 to now, also future predictions. Many other factors contribute but I will use pesticides in my visual representation.
Over the last 25 years, etymologists have set up tents all over German woodlands and meadows to observe natures insects. The average biomass of insects sampled in a 6-month period (May to October) has steadily decreased from 1.6 kilograms (3.5 pounds) (56 ounces) per trap in 1989 to just 300 grams (10.6 ounces) in 2014. 18.9% of the average biomass 25 years ago. This simulation will illuminate the devastating effects of damage to the bottom of the food chain.
-adjustable poison release
Goal: Predict hypothetical decline of insect population: how many years until there are none left.