ORL-30806 Operations Research and Logistics

Course

Credits 6.00

Language of instruction:

English

Assumed knowledge on:

ORL-20306 Decision Science 1.

Contents:

This course broadens in deepens the knowledge and skills acquired in ORL-20306 Decision Science 1. The global aim is to learn to deal with new (difficult) models and algorithms. The focus of the course is on supporting logistical decision processes in an industrial environment by means of quantitative models and techniques. Long-term as well as short-term management/control of good-flows and required production factors are studied. Some of the topics: location-allocation problems (strategic control level), production planning and inventory management (tactical control level), routing problems (operational control level), non-linear programming.

Learning outcomes:

After successful completion of this course students are expected to be able to:
- classify typical decision problems in logistics;
- deduce a quantitative model for presented decision problems in logistics;
- judge which algorithm is appropriate to solve the formulated problem;
- apply (newly) provided algorithms to calculate a solution to a provided decision problem;
- evaluate the effectiveness and efficiency of algorithms;
- select from OR journals an appropriate article on a prespecified topic, as preparation for thesis research activities;
- argue on the tenor of the selected OR article in a presentation.

Activities:

- studying the literature;
- acquiring knowledge, skills and insight by active participation in the tutorials;
- making exercises and acquiring skills by active participation in the tutorials and practical's;
- study with a group an article and present a summary (assignment).

Examination:

Written open book exam (100%).
Admission conditions to the written exam apply.

Literature:

Ghiani G, Laporte G, Musmanno R. (2013). Introduction to logistics systems management, 2nd ed. Wiley. 478 p. ISBN-10: 1119943388; ISBN-13: 978-1119943389.
Reader Computer Practical's Operations Research and Logistics (Blackboard).