ORL-30306 Decision Science 2


Credits 6.00

Teaching methodContact hours
Practical intensively supervised20
Course coordinator(s)ir. JC van Lemmen-Gerdessen
Lecturer(s)dr. ir. GDH Claassen
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


This course broadens and deepens the knowledge and skills acquired in ORL-20306 Decision Science 1. The topic of DS2 is decision making under uncertainty. This uncertainty can occur in many aspects of a decision problem: you do not know in advance how large demand for your product will be, you do not know in advance at which price you can purchase your raw materials, you do not know in advance which production capacity will be (just) enough for your needs.
In DS2 decision making under uncertainty is brought to you from three different views by three different chair groups: - Operations Research and Logistics: tries to make a quantitative model of a decision situation to help you take a good decision, and to evaluate alternatives.
- Business Economics: Analysis of decision alternatives reckoning with expected profit and with the attitude of the decision maker towards risk. Ranking alternatives.
- Information Technology: Many decision situations are so complicated that you cannot analyse them in a straightforward way. In such cases you can use simulation to study the behaviour of your system-with-uncertainty under each of your alternatives.
Some of the topics: stochastic dynamic programming, the value of information, queuing theory, stochastic linear programming, discrete simulation, heuristics.
Some of the applications: the milk chain, production planning, pest control, investment problems, and many more.

Learning outcomes:

After the course the students are expected to be able to:
- recognise and classify (typical) decision situations;
- select the appropriate methods for analyzing decision problems;
- formulate a quantitative model to generate a solution for a presented (decision) problem;
- apply the presented algorithms and techniques to calculate a solution to a provided decision problem;
- use the provided (simulation) software to solve decision problems;
- interpret the results of the calculations, simulations, or both.


- studying the reader;
- making exercises;
- acquiring knowledge and skills by active participation in the tutorials;
- acquiring skills in active participation in practicals;
- apply the newly acquired knowledge and skills in a case-study.


written exam.


Syllabus Decision Science 2, which will contain the course guide.

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 Processing5MO
MBEAgricultural and Bioresource EngineeringMSc5MO