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MIPLIBing: Seamless Benchmarking of Mathematical Optimization Problems and Metadata Extensions

Author

Listed:
  • Thiago Serra

    (Bucknell University)

  • Ryan J. O’Neil

    (nextmv)

Abstract

Public libraries of problems such as Mixed Integer Programming Library (MIPLIB) are fundamental to creating a common benchmark for measuring algorithmic advances across mathematical optimization solvers. They also often provide metadata on problem structure, hardness with respect to state-of-the-art solvers, and solutions with the best objective function value on record. In this short paper, we discuss some ways in which such metadata can be leveraged to create a seamless testing experience. In particular, we present MIPLIBing: a Python library that automatically downloads queried subsets from the current versions of MIPLIB, MINLPLib, and QPLIB, provides a centralized local cache across projects, and tracks the best solution values and bounds on record for each problem. While inspired by similar use cases from other areas, we reflect on the specific needs of mathematical optimization and discuss opportunities to extend benchmark sets to facilitate experimentation with different model structures.

Suggested Citation

  • Thiago Serra & Ryan J. O’Neil, 2020. "MIPLIBing: Seamless Benchmarking of Mathematical Optimization Problems and Metadata Extensions," SN Operations Research Forum, Springer, vol. 1(3), pages 1-6, September.
    • Handle: RePEc:spr:snopef:v:1:y:2020:i:3:d:10.1007_s43069-020-00024-1
    DOI: 10.1007/s43069-020-00024-1
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    References listed on IDEAS

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    1. Gerhard Reinelt, 1991. "TSPLIB—A Traveling Salesman Problem Library," INFORMS Journal on Computing, INFORMS, vol. 3(4), pages 376-384, November.
    2. Robert E. Bixby, 2002. "Solving Real-World Linear Programs: A Decade and More of Progress," Operations Research, INFORMS, vol. 50(1), pages 3-15, February.
    3. Richard Laundy & Michael Perregaard & Gabriel Tavares & Horia Tipi & Alkis Vazacopoulos, 2009. "Solving Hard Mixed-Integer Programming Problems with Xpress-MP: A MIPLIB 2003 Case Study," INFORMS Journal on Computing, INFORMS, vol. 21(2), pages 304-313, May.
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