Professional studies

Teaching language


Type of course


Recommended year of study


Total number of ECTS

5 cr

Competency aims

The aim of the course is...to learn practical methods for solving numerical, random-event problems in production and business by using simulation techniques. Such situations occur in real life in scheduling of production, in waiting lines for service, and in logistic supply chains.

Learning outcomes

At the end of the course the student is expected to be able to... - perform a physical simulation of a process - understand, and correctly select, probability distributions - build and run a mathematical simulation using a spreadsheet such as Excel - plan, build, debug, calibrate, run and validate a mathematical simulation using state-of-the art software, such as Simul-8 - dedice when to use, and when not to use, the simulation method to solve real-life problems

Course contents

What is simulation? When is it a good idea to apply simulation? What mathematical tools are available for simulation? Random numbers. Frequency distributions: rectangular, normal, exponential, Poisson. Useful software: Excel spreadsheet, Simul-8 dedicated software. Modeling and running a simulation. Interpreting the results of simulation. When not to simulate.

Prerequisites and co-requisites

A basic knowledge in mathematics is required. It is helpful to have some prior knowledge of statistics, economics and logistics.

Previous course names

Process Simulation, slightly varying versions, from 2003 to 2007.

Recommended or required reading

Course literature: Official web-based course notes by Henry Ericsson. Reference literature: Taha, Hamdy A. Operations Research - an introduction. Prentice Hall, USA. 6th edition, 1997. Mitrani, I. Simulation techniques for discrete event systems. Cambridge University Press, Cambridge 1982. Mendenhall, Reinmuth & Beaver. Statistics for management and economics. Duxbury Press. Belmont, Calif. 1996.

Study activities

  • Lectures - 30 hours
  • Exercise based learning - 30 hours
  • Laboratory lessons and tasks in a simulated environment - 43 hours
  • Individual studies - 30 hours


  • Total workload of the course: 133 hours
  • Of which autonomous studies: 30 hours
  • Of which scheduled studies: 103 hours

Mode of Delivery

Participation in tuition

Assessment methods

Reports and productions


Ericsson Henry


Ericsson Henry

Home page of the course


Group size

No limit

Assignments valid until

Until date 2009-04-16

The timetable of the course

The course will run in period 3.

Assessment methods

2009-04-09 - Reports and productions

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