WEBINAR / EVENT
Avoiding Numerical Issues in Optimization Models
Models with numerical issues can lead to undesirable results: slow performance, wrong answers or inconsistent behavior.
September 01 2022
WEBINAR / EVENT
Avoiding Numerical Issues in Optimization Models
Models with numerical issues can lead to undesirable results: slow performance, wrong answers or inconsistent behavior.
September 01 2022
WEBINAR / EVENT
Avoiding Numerical Issues in Optimization Models
Models with numerical issues can lead to undesirable results: slow performance, wrong answers or inconsistent behavior.
September 01 2022
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
Presented Materials
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
Presented Materials
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
Presented Materials
Speakers
Meet Your Expert Speaker
Learn from the best in the industry, bringing years of experience and groundbreaking insights to the forefront of AI personalization.
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.
Speakers
Meet Your Expert Speaker
Learn from the best in the industry, bringing years of experience and groundbreaking insights to the forefront of AI personalization.
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.
Speakers
Meet Your Expert Speaker
Learn from the best in the industry, bringing years of experience and groundbreaking insights to the forefront of AI personalization.
Senior Developer at Gurobi Optimization
Daniel Espinoza
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.
