It is time to refresh the standard benchmarking library for mixed integer programming - MIPLIB (http://miplib.zib.de)- so that it continues to reflect the state-of-the-art. We want you to play an active part in the process. You can contribute now and help shape the future of mixed integer programming by submitting your instances at https://miplibsubmissions.zib.de/.
Since its first release in 1992, MIPLIB has become a standard test set used to compare the performance of mixed integer linear optimization software and to evaluate the computational performance of newly developed algorithms and solution techniques. It has been a crucial driver for the impressive progress we have seen over the last decades, but seven years have passed since the last update in 2010.
While there were 134 out of 361 problems unsolved with the release of MIPLIB2010, there are only 76 unsolved instances left as of this writing, tendency falling. The latest release of FICO Xpress could solve the previously unsolved pigeon-19 in less than a second and moved three more instances from “hard” to “easy”. New challenges are needed!
Submit your instances at https://miplibsubmissions.zib.de/
MIPLIB2017 will be the sixth edition of the Mixed Integer Programming LIBrary. To continue the diversity and quality standards of the previous editions, the MIPLIB committee is looking for interesting and challenging (mixed-)integer linear problems from all fields of Operations Research and Combinatorial Optimization, ideally ones which have been built to model real-world problems. The goal of MIPLIB is and has always been, to give a broad coverage of the many different areas in which mixed integer programming is used to improve decision making.
We believe that there are many great MIP models out there which could fit the purpose of MIPLIB. Medium-hard MIPs that solve to optimality within a few minutes, hours or one or two days are the best candidates.
While certainly interesting, the following are not well-suited for MIPLIB:
- Simple models that solve within milliseconds to seconds
- Hard models where even the root LP problem cannot be solved within an hour
- Numerically challenging models such as those with huge coefficients, lots of singular bases etc., which are often not well-suited for benchmarking because of the sensitivity of potential solutions to numerical tolerances
- Pure LPs, quadratic problems and instances with SOSs - these don't qualify as true MIPs in the MIPLIB sense
- Specific instances of problems that exhibit strange behavior - if you have a number of instantiations of the same or similar models, with a mix of simple to medium to hard, it is best to submit them all, or at least a representative sample of them, but not only the outliers
Submit your instances at https://miplibsubmissions.zib.de/. The submission deadline is February 28, 2017.
MIPLIB 2010 was the first MIPLIB release that has been assembled by a larger committee with members from academia and industry. With MIPLIB2017, the group of participating institutions has grown even bigger; it is a joint initiative by Arizona State University, COIN-OR, CPLEX, FICO, Gurobi, Matlab, MIPCL, MOSEK, NuOPT, SAS, SCIP, and Zuse Institute Berlin. We believe that it is a great achievement to have such a huge variety of optimization experts working on a joint project.
Please contact Timo Berthold (firstname.lastname@example.org) with any questions about MIPLIB. Timo is a main developer of the FICO Xpress Optimizer and a committee member of MIPLIB2010 and MIPLIB 2017. Check out his blog about The Two Faces of Parallelism.