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351-0860-00L 3 Credits MSC D-MATH , D-MTEC

Robust Planning Methods in Operations Management

Lecturers & Examiners: PD Dr. Marco Laumanns
VVZ CR n/a

Last Updated: 2026-02-05 15:29:38

Abstract

This course covers quantitative model-based methods for robust planning. Focusing on problems of sequential decision making under uncertainty, techniques based on robust dynamic programming and stochastic control will be introduced and applied to planning problems from production and operations management.

Objective

Knowledge in quantitative methods for model-based planning under uncertainty. Awareness of the effects of uncertainty in the dynamics of a system, the concept of a plan, and the necessity to express and quantify preferences regarding uncertain outcomes. Ability to formally state decision problems under uncertainty and knowledge of the fundamental solution techniques based on stochastic dynamic programming. Ability to apply the methods to practical planning problems from production and operations management.

Content

Model-based planning. Concept of robustness and robust plans. Decision theory. Adaptive planning and flexibility. Sequential decision problems. Stochastic dynamic programming and stochastic control. Bellman's principle of optimality. Robust optimization and robust dynamic programming. Value iteration and policy iteration. Applications in production and operations management.

Resources

Lecture Notes

The lecture slides will be made available in PDF.

Literature

Bertsekas D. P. (2005): "Dynamic Programming and Optimal Control. Third Edition." Athena Scientific, Belmont

General Information

Language
English
Levels
MSC
Frequency
Yearly recurring

Examination

Type
session examination
Mode
written 90 minutes
Aids
Lecture slides (handouts), personal notes, calculator

Course Components

Type Title Time & Place Hours
lecture Robust Planning Methods in Operations Management
  • Tue 13:15-15:00 (HG E 22)
2 h weekly
exercise Robust Planning Methods in Operations Management
  • Tue 15:15-16:00 (HG E 22)
1 h weekly

Offered In