ORL-30306 Decision Science 2


Credits 6.00

Teaching methodContact hours
Independent study
Course coordinator(s)ir. JC van Lemmen-Gerdessen
Lecturer(s)dr. R Haijema
ir. JC van Lemmen-Gerdessen
dr. ir. MCM Mourits
drs. MR Kramer
Examiner(s)dr. ir. GDH Claassen
dr. ir. MCM Mourits
ir. JC van Lemmen-Gerdessen
drs. MR Kramer
dr. R Haijema

Language of instruction:


Assumed knowledge on:

ORL-20306 Decision Science 1.

Continuation courses:

ORL-30806 Operations Research and Logistics.


1. Multi-criteria decision making
Ways of dealing with problems that have several, mostly conflicting objectives. This topic also comprises Risk and Uncertainty, in order to incorporate into the decision making process the personal judgements of the decision maker about uncertainties and outcome-values.
2. Simulation
Many systems are so complex that you cannot optimize them in a straightforward, analytical way. Simulation increases the understanding of such a system by building a model of reality, and analysing its behaviour.
3. Approximation methods (heuristics)
In many cases problems are too big or too complex to find an optimal solution in a reasonable amount of time. In those cases we can use approximation methods (heuristics) that find relatively good solutions in a relatively short amount of time.
In Decision Science 2 three different chair groups participate:
- Operations Research and Logistics (ORL)
- Business Economics (BEC).
- Information technology (INF).
The methods and techniques will be demonstrated with examples from e.g. the milk chain, production planning, pest control, investment problems.

Learning outcomes:

After successful completion of this course students are expected to be able to:
- analyse an MCDM situation using multi-objective programming and compromise programming;
- apply the provided approximation methods to solve a small-scale problem;
- analyse a decision situation where risk and uncertainty occurs, using value of information, simulation, Bayesian updating, and utility theory;
- for a provided situation construct a simulation model in professional software;
- analyse the outcome of a simulation model;
- judge which decision making tool is appropriate in a given decision situation.


- studying the written materials;
- making exercises;
- acquiring knowledge and skills by active participation in the tutorials;
- acquiring skills in active participation in practicals.


Written closed book exam (100%) provided sufficient testimonial for practical assignment.
Details: see course guide.


G.D.H. Claassen; Th.H.B. Hendriks; E.M.T. Hendrix. (2007). Decision Science: Theory and applications. ISBN: 9789086860012. (also used in Decision Science I)
Reader Decision Science 2.

Restricted Optional for: BBCManagement and Consumer StudiesBScA: Management Studies5MO
MMEManagement, Economics and Consumer StudiesMScA: Management Studies5MO
MMEManagement, Economics and Consumer StudiesMScD: Management, Innovation and Life Sciences5MO
MMEManagement, Economics and Consumer StudiesMScD: Management, Innovation and Life Sciences5MO
MFTFood TechnologyMScH: Sustainable Food Process Engineering5MO
MBEBiosystems EngineeringMSc5MO