Speedups: comparing against moving targets

[This is post #1 of 2 that were inspired by a tweet from IBM’s Jean-François Puget] Over the course of my studies, I had to develop custom solution methods for very challenging supply chain network design problems. While striving to create better models and solution algorithms, I had to compare the performance of my approach […]

Using more processors does not necessarily lead to reduced run times on CPLEX

This post takes a look at performance variability issues when scaling up the number of processors assigned to the CPLEX MIP solver. I summarize results from a few computational experiments we’ve made. I show that while increasing the number of processor cores  results in quicker runs on average, but the effect on individual instances is […]

The heuristic ‘feel’ of MIP solvers

MIP solvers are now more powerful than ever. Models that were considered very difficult 10 years ago are now routine work. They are solved efficiently, and performance is pretty stable from one instance to another. I also like to use solvers on more difficult models and instances. On large classes of models, you still get a very […]