ORL-20306 Decision Science 1

Course

Credits 6.00

Teaching methodContact hours
Lectures24
Practical extensively supervised12
Practical intensively supervised12
Tutorial24
Self-study
Course coordinator(s)dr. ir. GDH Claassen
Lecturer(s)dr. ir. GDH Claassen
ir. JC van Lemmen-Gerdessen
dr. A Kanellopoulos
Examiner(s)dr. ir. GDH Claassen

Language of instruction:

English

Continuation courses:

ORL-30306 Decision Science 2; ORL-31306 Advanced Supply Chain Management; ORL-30806 Operations Research and Logistics.

Contents:

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.

Activities:

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

Examination:

Written open book exam (100%).

Literature:

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

ProgrammePhaseSpecializationPeriod
Compulsory for: BBCManagement and Consumer StudiesBSc1AF
BATBiosystems EngineeringBSc2AF
Restricted Optional for: BFTFood TechnologyBSc1AF
MMEManagement, Economics and Consumer StudiesMScD: Management, Innovation and Life Sciences1AF, 2AF
MMEManagement, Economics and Consumer StudiesMScC: Economics, Environment and Governance1AF, 2AF
MMEManagement, Economics and Consumer StudiesMScA: Management Studies1AF, 2AF
MMEManagement, Economics and Consumer StudiesMScD: Management, Innovation and Life Sciences1AF, 2AF
MBTBiotechnologyMScD: Process Technology1AF, 2AF
MinorPeriod
Compulsory for: WUSCMBSc Minor Supply Chain Management1AF
Restricted Optional for: WUABMBSc Minor Agricultural Business Management1AF