Just a LP, really?

In recent talks in scientific conferences, I saw some people dissmiss pure linear programming (LP) models as being easy and primitive. I often got said “oh, that’s just a LP”. Linear programming is put in the box of solved problems, like some network problems such as the (pure) shortest path or max flow. In fact, I think […]

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 […]

When optimal is not enough

Currently I work with Professor Mikael Rönnqvist from Université Laval on an inventory and transportation management problem from a forest products company.  As a large scale commodity products company, much of its focus is on reducing logistics costs while improving its efficiency and service such as on-time deliveries. As such, we are developing a decision […]

Exam design problem

For students, the final exam week is probably the most stressful time of a semester. They often have multiple exams over consecutive days and need to split their last-minute study and preparation time over these topics. I must confess that I also feel some stress during this week. Here’s why. First, designing an exam is not so […]

The day I put my hand into the shredder

…or so to speak. Recently, I’ve been working (in collaboration with two people) on a production planning model for a network of sawmills. It is not yet customized for a particular company. We came to this particular model after a few meetings, and it is rather clean and easy to read. The project went very […]

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 […]

In-house testing of CPLEX distributed MIP

Distributed optimization is now part of standard CPLEX releases. In fact, it’s been there since release 12.5. I decided to do some experiments and post on this after seeing Daniel Junglas’ talk at the German OR Conference in September, but writing the post has been delayed until recently. I summarize the results of my experiments and compare those […]

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 […]