IDA715 Discrete Event Simulation (Spring 2024)

About the course

The purpose of this course is to provide theoretical and practical tools for discrete-event simulation of business processes. A special emphasis is placed on the use of simulation software (e.g. Arena, Anylogic). The course will cover the following topics:

• Introduction to queueing theory.
• Discrete events (random, deterministic), event scheduling and pseudo-random number generation.
• Input data analysis.
• Logical processes and flow management in modelled systems.
• Model implementation using simulation software.
• Model verification and validation.
• Design of experiments.
• Performance metrics and analysis of output results.
• Simulation as a decision-support tool.

The course includes a number of examples from logistics and supply chain management.

The course is connected to the following study programs

• Master of Science in Logistics
• Master of Science in Sustainable Energy Logistics
• Exchange programme - Master's level

Recommended requirements

Knowledge of statistics and basics of computer programming will be an advantage.

The student's learning outcomes after completing the course

Knowledge

• Understand the characteristics of discrete-event simulation methodology, as well as the effects of uncertainty on performance of modelled systems.
• Understand the simulation modeling software environment, including handling of input and output data, modeling blocks and flowcharting capabilities, experiment design functionality.

Skills

• Build own simulation models in order to analyze processes in logistics and supply chain management.
• Perform input data collection and analysis.
• Design, implement, and validate simulation models.
• Incorporate uncertainty into simulation models.
• Analyze and calibrate models based on observed input data.
• Interpret simulation results and draw conclusions.

General competence

• Recognize real-world problems and situations where discrete-event simulation models can be used to improve decision making.

Forms of teaching and learning

The teaching is based on lectures with computer exercises. Three hours of teaching per week. 

Coursework requirements - conditions for taking the exam

• Mandatory coursework: Assignment(s)
• Courseworks given: 1
• Courseworks required: 1
• Presence: Required
• Comment: A compulsory exercise using the course’s simulation software with a written report.

Examination

• Form of assessment: Home assessment

• Proportion: 100%

• Duration: 4 weeks

• Grouping: Group

• Grading scale: Letter (A - F)

• Supported material: All printed and written materials 

Syllabus

The current reading list for 2024 Spring can be found in Leganto