ORL-20306 Decision Science 1


Credits 6.00

Teaching methodContact hours
Independent study0
Course coordinator(s)dr. D Krushynskyi
dr. ir. GDH Claassen
Lecturer(s)dr. D Krushynskyi
dr. A Kanellopoulos
dr. ir. GDH Claassen
ir. JC van Lemmen-Gerdessen
N Nguyen Quoc Viet
dr. ir. PM Slegers
Examiner(s)dr. ir. GDH Claassen

Language of instruction:


Continuation courses:

ORL-30306 Decision Science 2; ORL-33306 Decision Science for Technology; YSS-32806 Advanced Supply Chain Management; ORL-30806 Operations Research and Logistics.


Decision Science is dealing with quantitative methods and techniques to support decision processes.

Global aims are: getting familiar with and acquiring basic insight and understanding of mathematical programming (i.e. MP-based) models and techniques in Operations Research, recognize where typical decision problems occur, develop models and apply solution techniques to solve the models. The background of the methods is discussed in the course and it is indicated how they can be applied to practical decision problems. The modelling is illustrated from many decision problems of firms, consumers, governments and non-profit organisations.

Subjects: Sketch of some typical decision problems: fodder composition, location-allocation problems, transportation problems, supply chain problems, household budgeting, production planning, etc. Linear algebra with respect to sets of equalities will be refreshed. Linear programming, graphical method, simplex method, duality, shadow prices, sensitivity analysis. Integer Linear programming: the Branch-and-Bound method. Multi-criteria decision problems and Goal programming. Deterministic dynamic programming; Bellman equation. Correct interpretation of results is an important aspect.

Learning outcomes:

After successful completion of this course students are expected to be able to:
- recognize situations in which typical decision problems occur;
- distinguish the different classes of decision problems;
- construct an optimization model based on a verbal description of a decision problem;
- apply the studied algorithms to calculate a solution to minor provided problems;
- demonstrate insight with respect to solution techniques;
- analyse the outcome of the solution techniques for small-scale problems;
- translate MP-based models in state of the art, design oriented optimization tools.


- study written material;
- making exercises;
- using OR software in computer practicals;
- following lectures with an active attitude.


Written open book exam (100%). See Course guide for additional rules and regulations.


G.D.H. Claassen; Th.H.B. Hendriks; E.M.T. Hendrix. (2007). Decision Science: Theory and applications. ISBN 978-90-8686-001-2.

Compulsory for: BBCManagement and Consumer StudiesBSc1AF
BATBiosystems EngineeringBSc2AF
Restricted Optional for: BFTFood TechnologyBSc1AF
MMEManagement, Economics and Consumer StudiesMScD: Spec. D - Management in Life Sciences1AF, 2AF
MMEManagement, Economics and Consumer StudiesMScD: Spec. D - Management in Life Sciences1AF, 2AF
MMEManagement, Economics and Consumer StudiesMScD: Spec. D - Management in Life Sciences1AF, 2AF
MBTBiotechnologyMScD: Spec. D - Process Technology1AF
Compulsory for: WUSCMBSc Minor Supply Chain Management1AF
Restricted Optional for: WUABMBSc Minor Agricultural Business Management1AF