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An algorithm for binary linear chance-constrained problems using IIS

Author

Listed:
  • Gianpiero Canessa

    (Universidad Adolfo Ibañez)

  • Julian A. Gallego

    (AT Kearney Inc)

  • Lewis Ntaimo

    (Texas A&M University)

  • Bernardo K. Pagnoncelli

    (Universidad Adolfo Ibañez
    IEMS Department, Northwestern University)

Abstract

We propose an algorithm based on infeasible irreducible subsystems to solve binary linear chance-constrained problems with random technology matrix. By leveraging on the problem structure we are able to generate good quality upper bounds to the optimal value early in the algorithm, and the discrete domain is used to guide us efficiently in the search of solutions. We apply our methodology to individual and joint binary linear chance-constrained problems, demonstrating the ability of our approach to solve those problems. Extensive numerical experiments show that, in some cases, the number of nodes explored by our algorithm is drastically reduced when compared to a commercial solver.

Suggested Citation

  • Gianpiero Canessa & Julian A. Gallego & Lewis Ntaimo & Bernardo K. Pagnoncelli, 2019. "An algorithm for binary linear chance-constrained problems using IIS," Computational Optimization and Applications, Springer, vol. 72(3), pages 589-608, April.
    • Handle: RePEc:spr:coopap:v:72:y:2019:i:3:d:10.1007_s10589-018-00055-9
    DOI: 10.1007/s10589-018-00055-9
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    References listed on IDEAS

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