Бакалавриат
2023/2024
Имитационное моделирование в AnyLogic
Статус:
Курс по выбору (Управление цепями поставок и бизнес-аналитика)
Направление:
38.03.02. Менеджмент
Кто читает:
Департамент бизнес-информатики
Где читается:
Высшая школа бизнеса
Когда читается:
4-й курс, 1 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для всех кампусов НИУ ВШЭ
Преподаватели:
Заходякин Глеб Викторович
Язык:
английский
Кредиты:
4
Контактные часы:
40
Course Syllabus
Abstract
Students of the discipline "Simulation AnyLogic" will get theoretical knowledge and practical skills in the application of different paradigms of simulation modeling (process and agent-based) to solve problems in various business areas. The students will learn how to build simulation models using the market-leading multi-approach simulation modeling tool - Anylogic. Students will learn how to plan and execute different types of simulation experiments. An important part of the course is the study of practical cases of using simulation for solving real-world business problems. And at the end of the course students will implement their own team project on solving an applied business problem using simulation modeling. This project is presented for defense at the exam.
Learning Objectives
- To solve applied business problems using simulation modeling method and tools
- To develop simulation models and to conduct simulation experiments using Anylogic environment
Expected Learning Outcomes
- Can list the paradigms of simulation modeling and explain their differences in their own words
- Can articulate in their own words the essence of the simulation modeling method and its difference from the analytical approach
- Can name three market-leading simulation modeling tools
- Can develop a process simulation model in Anylogic based on the process description
- Can articulate in their own words the essence of the process approach in simulation modeling
- Can collect and interpret simulation model outputs correctly
- Can create animation and user interface for a simulation model in Anylogic
- Can explain in their own words the purpose and applications of Anylogic's specialized industry libraries
- Can create agent models in Anylogic and specify agent behavior using state diagrams and process library blocks
- Can create agent-based models in Anylogic using GIS map
- Can correctly collect and interpret output metrics in agent-based models
- Can formulate in their own words the essence of the agent-based approach in simulation modeling
- Can apply built-in and external tools for simulation experiment data collection and processing in Anylogic
- Can explain in their own words the influence of Anylogic's random number generator settings on the model's behavior, as well as the rules for selecting the correct settings
- Can select appropriate random number distributions for a simulation model based on input data analysis
- Can select the number of simulation runs required to achieve a given accuracy
- Can set up an optimization experiment in Anylogic correctly
- Can compare different variants of the modeled system using the method of statistical hypothesis testing and the parameter variation experiment
- Can present the results of the simulation study to the business customer
- Can develop a conceptual description of a simulation model
- Can describe in their own words the essence of the stages of a simulation study
Course Contents
- Method and tools of simulation modeling
- Process modeling
- Agent based modeling
- Simulation experiment
- Simulation modeling as a method of solving business problems
Assessment Elements
- Case PresentationThis is a group-based assignment. The goal is to analyze and to present a practical case on using simulation to solve business problems.
- ParticipationParticipation in discussions of reports (questions to speakers) and solving problems proposed during the session or for a self-study
- Homework AssignmentThe purpose of homework is to develop practical skills in developing simulation models in Anylogic environment and justifying managerial decisions on their basis
- QuizThe quiz is designed to assess the degree of assimilation of theoretical material and mastery of the Anylogic modeling tool. The quiz is conducted in the classroom at the last lesson.
- ProjectThis is a group-based assignment for groups of up to 3 people. The project teams solve independently chosen or proposed by the teacher business problem with the involvement of simulation modeling
Interim Assessment
- 2023/2024 1st module0.15 * Case Presentation + 0.25 * Homework Assignment + 0.2 * Participation + 0.3 * Project + 0.1 * Quiz
Bibliography
Recommended Core Bibliography
- Davide Secchi, Martin Neumann. Agent-Based Simulation of Organizational Behavior. New Frontiers of Social Science Research. 2016. Springer. https://proxylibrary.hse.ru:2184/search?query=organizational+behavior
- Klein, M., Frey, U. J., & Reeg, M. (2019). Models Within Models-Agent-Based Modelling and Simulation in Energy Systems Analysis. Journal of Artificial Societies & Social Simulation, 22(4), 1–18. https://doi.org/10.18564/jasss.4129
- Ross, S. M. (2006). Simulation (Vol. 4th ed). Amsterdam: Academic Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=320768
- Ruiz Zúñiga, E., Urenda Moris, M., & Syberfeldt, A. (2016). Production Logistics Design and Development Support : A Simulation-Based Optimization Case Study (WIP). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.CF78A7E8
- Xiao, N., Ni, C. D., & Guo, S. J. (2017). Modelling and Simulation for Production Logistics System in Industrial Enterprises Based on Hybrid Network. International Journal of Simulation Modelling (IJSIMM), 16(1), 157–166. https://doi.org/10.2507/IJSIMM16(1)CO3
Recommended Additional Bibliography
- Simulation with arena, Kelton, W. D., 1998
- Имитационное моделирование : теория и технологии, Рыжиков, Ю. И., 2004
- Имитационное моделирование : учебник и практикум для акад. бакалавриата, Акопов, А. С., 2015
- Имитационное моделирование систем - искусство и наука, Шеннон, Р., 1978
- Имитационное моделирование, Лоу, А. М., 2004