Single-Course English 5 ECTS

Stochastic Simulation

Overall Course Objectives

Numerical simulation is used for solving problems which are so complex that a theoretical model of the system cannot be solved by analytical methods. The goal is to enable the student to formulate a model of a real-life problem, implement and validate this model on a computer, and perform experiments with the computer model. Emphasis is put upon models involving stochastic elements, which are simulated by so-called Monte Carlo methods.

Learning Objectives

  • Apply build-in random number generators in various software products
  • Implent algorithms for random number generation from various distributions
  • Perform simple statistical analysis of simulated data
  • Apply simulation based statistical techniques like bootstrap and Markov Chain Monte Carlo
  • Apply simulated annealing as a heuristic method for minor optimization problems with discrete variables
  • Develop and implement simulation procedures for simple technical systems using the event by event principle
  • Perform verification of a programme for simulation
  • Perform validation of a simulation model
  • Plan and execute a simulation study for a specific part or function of some (technical) system
  • Apply techniques for variance reduction in a simulation study
  • Present the results of a simulation study writtenly or verbally

Course Content

The first six to seven days deals with theory and exercises, followed by a case-study during the remaining part of the last two weeks. Attendance is mandatory for the first period of the course.
Theory: The modelling process, methods of solution, random number generation, sampling from statistical distributions. Discrete simulation: Time-true simulation, event-by-event principle, variance reduction. Case-studies: Operations research real-life problems, e.g. performance of data- and telecommunication systems, production planning, inventory control, optimal stochastic control etc.

Recommended prerequisites

02402, or a similar course in elementary statistics. Basic programming skills.

Teaching Method

Lectures, exercises and project work.


See course in the course database.





3 weeks




DTU Lyngby Campus

Course code 02443
Course type Candidate
Semester start Week 23
Semester end Week 26
Days Mon-fri 8:00-17:00

7.500,00 DKK