How problematic are your Big M constraints? an experiment [primal]

This post investigates whether it is still relevant to be careful about the coefficients used in so-called Big M constraints when formulating mixed-integer programming (MIP) models. I make some experiments with two-echelon supply chain design models to show that using too large values often cause the models to be harder to solve. The impact is much greater […]

A relevant #orms resolution for 2017: Update your solvers!

Making resolutions during the New Year has become something of a tradition. Some are followed, many are not. Here is one resolution I took years ago that has been pretty relevant. I would encourage you to use it as well : Update your solvers whenever a new version is released. Like, every time. It’s worth […]

The recommendation game [primal]

People who teach or supervise students have a tremendous influence on what solvers get adopted by the operations research / industrial engineering community. Once they finish their studies, many students will continue to use the tools they have learned in school, for many reasons. First, it is simply the most efficient strategy to adopt. Also, […]

Facility location : not so difficult (with the proper tools)

In a previous post, I generated a few capacitated facility location instances (CFLP) and I ran these through MIP solvers. The instances were solved pretty quickly overall. In a comment, professor Matteo Fischetti suggested I compare my results with some instances from the literature, which I did. Overall, the results are quite fast; CPLEX takes only 21 […]

Facility location : mistake, issue and results

About two weeks ago, I generated a few capacitated facility location instances (CFLP) for some students to play with. When I ran these through the CPLEX and Gurobi solvers, all of them were solving very quickly. Gurobi in fact seemed to find the optimal solution during the presolve stage. I made a quick blog post […]

Facility location : presolved to optimality!

  ** IMPORTANT NOTICE ** This post has temporarily been suspended as some readers noticed potential problem with the model files. I will issue a corrected post shortly. I am sorry for any inconvenience. Marc-André

OR in the field: two challenges

This post presents some thoughts about doing applied operations research together with companies. It’s a lot of work, to be sure, but it’s also a lot of fun. Some of my colleagues tease me about not being often at my office. While it’s true that I split my office time between the research center and the buisness […]

Performance variability: consequences

If you work on difficult mixed-integer programming (MIP) models, you have experienced performance variability. This refers as the impact on performance of seemingly performance neutral changes induced in the model or the solver. Part 1 of this series presented the problem and its relevance, and part 2 provided some readings related to the topic. This […]

Performance variability: good readings

If you work on difficult mixed-integer programming (MIP) models, you have experienced performance variability. This refers as the impact on performance of seemingly performance neutral changes induced in the model or the solver. Part 1 of this series presented the problem and its relevance. This post presents some good readings related to the topic. Many thanks […]

Performance variability defined

These days, it seems that one of the most simple and effective ways to tackle difficult mixed-integer programming (MIP) models is to run the model on a state-of-the-art solver with different random seeds. It is very easy to implement and often provides better improvement than tuning the solver or using custom heuristics or solution procedures. This […]