English

Verifying Integer Programming Results

Optimization and Control 2019-01-03 v2 Discrete Mathematics Mathematical Software

Abstract

Software for mixed-integer linear programming can return incorrect results for a number of reasons, one being the use of inexact floating-point arithmetic. Even solvers that employ exact arithmetic may suffer from programming or algorithmic errors, motivating the desire for a way to produce independently verifiable certificates of claimed results. Due to the complex nature of state-of-the-art MILP solution algorithms, the ideal form of such a certificate is not entirely clear. This paper proposes such a certificate format, illustrating its capabilities and structure through examples. The certificate format is designed with simplicity in mind and is composed of a list of statements that can be sequentially verified using a limited number of simple yet powerful inference rules. We present a supplementary verification tool for compressing and checking these certificates independently of how they were created. We report computational results on a selection of mixed-integer linear programming instances from the literature. To this end, we have extended the exact rational version of the MIP solver SCIP to produce such certificates.

Keywords

Cite

@article{arxiv.1611.08832,
  title  = {Verifying Integer Programming Results},
  author = {Kevin K. H. Cheung and Ambros Gleixner and Daniel E. Steffy},
  journal= {arXiv preprint arXiv:1611.08832},
  year   = {2019}
}

Comments

Zuse Institute Berlin, Takustr. 7, 14195 Berlin, November 2016, http://nbn-resolving.de/urn:nbn:de:0297-zib-61044