Mathematical Programming Modelling

• Analyze decision problems to identify the problem type and formulate an appropriate mathematical model
• Formulate Linear Programming Problems
• Formulate Mixed Integer Linear Programming Problems
• Understand and formulate Stochastic Programming models
• Implement Stochastic Programming models and solve them with Julia/JuMP
• Understand and formulate Multi-Objective models
• Implement Multi-Objective models and solve them with Juia/JuMP
• Evaluate the solutions obtained with Julia/JuMP

The theoretical background from Introduction to Operations Research (42101) is supplemented by introducing a standard program modelling system for formulating and solving mathematical models, i.e. Linear Programming models, Integer Linear Programming models, and biobjective optimization problems. The exercises used in the course increase in difficulty as the course progresses.

42101, or a similar course in Introductory Operations Research. You are expected to be familiar with linear programming prior to the course.

Lectures and exercises

NOTE:

The official start date is 6/1 2025. We expect all student to show up on there first day of the course.

Before the course we expect all students to have Julia/JuMP and VS-code installed on their computer and have tried to execute basic LP/MIP models in Julia/JuMP before the start of the course.

We will send self study material with exercises in our welcome email. Students whose OR experience is a bit rusty, can benefit (a lot) from doing these exercises before the course.

We expect ALL students who participate in the course to know the basics of Linear Programming (LP) and Mixed Integer Programming (MIP). If you have only little or no experience with LP/MIP and/or Julia/JuMP, you can expect this course TO BE VERY DIFFICULT.