Optimization Online


An algorithm for binary chance-constrained problems using IIS

Gianpiero Canessa (gianpiero.canessa***at***edu.uai.cl)
Julián Gallego (julian.gallego***at***atkearney.com)
Lewis Ntaimo (ntaimo***at***tamu.edu)
Bernardo Pagnoncelli (bernardo.pagnoncelli***at***uai.cl)

Abstract: We propose an algorithm based on infeasible irreducible subsystems (IIS) to solve general binary chance-constrained problems. By leverag- ing on the problem structure we are able to generate good quality upper bounds to the optimal value early in the algorithm, and the discrete do- main is used to guide us eciently in the search of solutions. We apply our methodology to individual and joint binary chance-constrained prob- lems, 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.

Category 1: Stochastic Programming

Category 2: Integer Programming (0-1 Programming )

Citation: https://link.springer.com/article/10.1007/s10589-018-00055-9?wt_mc=Internal.Event.1.SEM.ArticleAuthorOnlineFirst&utm_source=ArticleAuthorOnlineFirst&utm_medium=email&utm_content=AA_en_06082018&ArticleAuthorOnlineFirst_20190105

Download: [PDF]

Entry Submitted: 11/30/2017
Entry Accepted: 11/30/2017
Entry Last Modified: 11/27/2019

Modify/Update this entry

  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository


Coordinator's Board
Classification Scheme
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Optimization Society