Open question: tuning for hard instances

This is a rather short post on an open question, one I’ve been thinking about for some time. Automated tuning tools for MIP solvers have been around for the last few years. During that time, I have used these tools – and sometimes seen them used – to reduce run times for various types of […]

Can the CPLEX tuning tool help solving hard models?

The CPLEX MIP Solver has had a tuning tool for some time. For those new to the concept, the tuning tool tries different parameter settings and seeks to find good parameters for the solver for a given optimization model. I have tested the tuning tool on 10 relatively difficult-to-solve models. By difficult, I mean models […]

Four uses for automated tuning of solvers

I only recently started working with automated tuning tools, either for metaheuristics or MIP solvers. I find the value proposal quite appealing, as it could remove the need for some time-consuming tasks that I don’t enjoy doing. However, after a few experiments I quickly realized that I took the wrong approach to reap the value […]

Some experiments with CPLEX automated tuning tool

Tuning strategies to get the most out of a solver seem an important issue to me. I a recent post, I looked at a strategy consisting of emphasizing cutting plane types that were generated by CPLEX using default settings. Following a suggestion from Paul A. Rubin, I decided to give a try with CPLEX’s automated tuning tool. […]

Tuning cut strategies: is it worth the effort?

When solving mixed-integer (MIP) models, one of the questions I ask myself (and I have been asked) is how good are the solver’s default parameters parameters for a given class of models. This is a rather natural question to ask when you realize how many parameters a solver has. We are constantly looking at ways […]