GRA 4138 Business Simulation Analysis
GRA 4138 Business Simulation Analysis
The course objective is to familiarize the students with computer-based simulation methodologies and tools used in business settings characterized by uncertainty and variability. The main focus will be on discrete-event, agent-based and Monte Carlo simulations.
- To identify, argue and interpret the use of simulation models, including discrete-event, agent-based and Monte-Carlo, in real world cases
- To modelling and analyse various systems using discrete-event simulation, agent-based simulation and Monte-Carlo techniques and tools
- To interpret and demonstrate outputs of the models effectively
- To carry out sensitivity analysis, optimization and calibration by using simulation
- To build and visualize simulation models and experiments in AnyLogic
- To identify real-world problems to which simulation methods are useful and relevant
- To understand and appreciate the way uncertain and variable factors affect performance of various systems and how simulation helps to model, design, improve and analyse such systems
- Introduction to simulation
- Anylogic modeling environment
- Discrete-event simulation
- Agent-based simulation
- Calibration, optimization and parameter variation experiments
- Pedestrian, process, material handling and traffic modeling libraries in Anylogic
- Monte-Carlo simulation
- Simulation in practice
- The course consists of lectures, exercises, presentations and discussions.
- The course is mostly held in the form of learning-by-doing.
- Students build different models in Anylogic step-by-step in the class and extend the models out of the class.
- There will be guest lectures by practitioners about real-world applications of simulation.
Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class.
Students must have a computer with them in all of the lectures. The following softwares must be installed on the computers:
- Anylogic (Personal Learning Edition)
- Microsoft Excel
All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have spesific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.
Covid-19
Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.
Teaching
Information about what is taught on campus and other digital forms will be presented with the lecture plan before the start of the course each semester.
- Basics of probability and statistics theory
- Basics of Microsoft Excel (formulas, addresses and functions)
- Although it is not a mandatory prerequisite, and students will learn as much programming (Java) as they require during the course, some basic experience with a programming language could be useful
| Assessments |
|---|
Exam category: Submission Form of assessment: Written submission Weight: 100 Grouping: Group (1 - 3) Duration: 1 Semester(s) Exam code: GRA 41381 Grading scale: ECTS Resit: Examination when next scheduled course |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.
Groups with fewer than 3 members will be allowed only in exceptional cases.