Course RO: Robust Optimisation

Time:	Monday 13:15–15:00
Period:	23 February 2026 – 11 May 2026 with the exception of 6 April and 27 April
Location:	All LNMB courses take place on the Campus Utrecht Science Park. Room HFG 611, Hans-Freudenthal building, Budapestlaan 6, 3584 CD Utrecht
Lecturers:	Dr. Frans de Ruiter (Wageningen University & Research and ASML) and Dr. Ahmadreza Marandi (Eindhoven University of Technology)

Course description

We are living in a world with lots of uncertainties. Weather conditions, prices, and traffic jams are only a few uncertainties that we are encountering in our daily life. Societal and industrial parties are also facing uncertainties in demands, costs, and many more parameters on which their revenues based. So, the important question is "how to make decisions in dynamic uncertain environments?"

The goal of this course is to teach students how to answer this question using "robustness," which is a concept that helps us to make decisions that are not vulnerable to the changes in the uncertain parameters. So, the first and the most important concept that will be taught in this course is Robustness in Optimization problems

The main topics treated are:

Uncertain (mixed integer) linear optimization (LO) problems

Data uncertainty in LO
Tractability of robust counterparts
Non-affine perturbations
Applications in logistics, marketing, finance, engineering
Data driven uncertainty sets

Uncertain nonlinear optimization problems

Tractability of robust counterparts
Examples

Robust adjustable multistage optimization

Adjustable robust counterpart
Affine policies
Finitely adaptive policies

Applications

Examples of how to code in python with notebooks
Robust location-transportation problem
Robust supply chain planning

Literature

Handouts
Lecture notes on Robust Optimization, by Dimitris Bertsimas and Dick den Hertog.

Prerequisites

Knowledge of basic linear algebra
Knowledge of linear programming and duality
Basic knowledge of convex analysis and non-linear optimization
Basic programming (python preferred)

Examination

Two take home problems.

Website for the course:

Website RO

Address of the lecturers

Dr. Frans de Ruiter
Operations Research and Logistics Group
Wageningen University & Research
E-mail: frans.deruiter@wur.nl

Dr. Ahmadreza Marandi
Department of Industrial Engineering & Innovation Sciences
Eindhoven University of Technology
E-mail: a.marandi@tue.nl