Avoiding Numerical Issues in Optimization Models

Avoiding Numerical Issues in Optimization Models

Models with numerical issues can lead to undesirable results: slow performance, wrong answers or inconsistent behavior.

Webinar Summary

Models with numerical issues can lead to undesirable results: slow performance, wrong answers or inconsistent behavior. When solving a model with numerical issues, tiny changes in the model or computer can make a big difference in the results. In this 45-minute long webinar, you will learn about Gurobi guidelines on numerical issues, how they impact your solutions and, most importantly, how to avoid them.

In this webinar, you will learn about:

  • What numerical issues are, including an overview of Gurobi guidelines
  • The impact numerical issues can have on your solutions
  • How to identify numerical issues within a model
  • How to avoid (most of) them by reformulating your model

Presenter

Presenting this webinar is Dr. Daniel Espinoza, Senior Developer at Gurobi Optimization.

Dr. Espinoza holds a Ph.D. in Operations Research from Georgia Institute of Technology. He has published numerous papers in the fields of mathematical programming, computer optimization and operations research. Prior to joining Gurobi, he was Associate Professor in the Department of Industrial Engineering at the Universidad de Chile.

Presented Materials

Download the materials associated with this webinar.