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An algorithm for binary linear chance-constrained problems using IIS

  • Gianpiero CanessaEmail author
  • Julian A. Gallego
  • Lewis Ntaimo
  • Bernardo K. Pagnoncelli
Article

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.

Keywords

Chance-constrained programming Infeasible irreducible subsystems Integer programming 

Notes

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Universidad Adolfo IbañezSantiagoChile
  2. 2.AT Kearney IncChicagoUSA
  3. 3.Texas A&M UniversityCollege StationUSA
  4. 4.Universidad Adolfo IbañezSantiagoChile
  5. 5.IEMS Department, Northwestern UniversityEvanstonUSA

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