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 Problems
• Understand Multiobjective Optimization and formulate biobjective optimization problems
• Implement and solve the developed mathematical models using Julia/JuMP
• Evaluate the solutions obtained with Julia/JuMP
• Describe mathematical models and illustrate their solutions in a report

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 first 7-9 days of the course are used to introduce the modelling language. The rest of the course is the used to model and solve a number of semi-realistic optimization problems.

42101, or a similar course in Introductory Operations Research

Lectures and project work

NOTE:

The officially starts 2/1 2024. We expect all student to show up for the course, AT THE LATEST Thursday 4/1 2024, in the morning.

Before the course we expect all students to have Julia/JuMP and VS-code installed on their computer.

We will send self study material in our wellcome email. Students who’s OR experience is a bit rusty, can benefit from doing these exercises 2/1 (or during the Christmas holiday).

We expect ALL students who participate in the course to know the basics of Linear Programming (LP) and Mixed Integer Programming (MIP). Furthermore, we expect that ALL students have Julia/JuMP installed on their laptop and that all students have tried to execute basic LP/MIP models in Julia/JuMP before the start of the course. If you have only little or no experience with LP/MIP and/or Julia/JuMP, you can expect this course to be rather work intensive.