What are Big M constraints? [dual]

This post presents a class of constraints that are used very often in mixed-integer programming (MIP) models. I explain what they are, why they are important and why using too large values for the big M is problematic. The associated primal post presents some experiments that outline how modern solvers handle unnecessarily large values of […]

The recommendation game [dual]

People who teach or supervise students have a tremendous influence on what solvers get adopted by the community. Once they finish their studies, many students will continue to use the tools they have learned in school; it is simply more efficient. In this post, I explain the reasons behind the choice of tools I use in class. […]

In-house testing of the Gurobi 6 distributed MIP [dual]

Distributed optimization is now part of the Gurobi 6.0 release. In today’s post, I talk about some tests I ran with the distributed MIP algorithm. The associated primal post discusses results presented by Gurobi at the INFORMS 2014 Annual conference.  Don’t worry, the next set of posts will cover the same topic, this time with CPLEX. Overall, it […]

Building the perfect MIPping machine [dual]

Yesterday’s post explained why I prefer to run solver on fast machines over big machines and gave a short example why. In today’s post, I provide some very personal guidelines on how to determine what kind of machine you might need to solve MIPs.  Beware: this post is more based on personal experiences than hard […]

Three value creation models in the OR field [dual]

I a previous primal post, I have described three generic types of value creation configurations: the shop, the chain and the network, as characterized in Stabell & Fjeldstad (1998). In this post, I apply these concepts to key players in the field of Operations Research. While names used are fictional, some players may recognize themselves in […]

Testing a solver based on local search [dual]

This post discusses some challenges associated with testing a solver based on local search heuristics. Local search is quite different from mathematical programming-based solvers and it should be tested accordingly. The associated primal post (not yet published) presents the results of my experiments with LocalSolver 3.0. Local Search VS MI(N)LP: Apples and Oranges First thing […]

5 reasons why solver developers should not listen (too much) to academia [dual]

We academia are very eager to offer advice. Here are a few reasons why solver developers should sometimes refrain from listening too much to what academia has to say. I don’t mean ignoring scientific literature, but rather “advice” and requests for features from graduate students and professors. You can get a set of arguments supporting […]