An algorithm for binary linear chance-constrained problems using IIS
Canessa
G
author
Gallego
J
A
author
Ntaimo
L
author
Pagnoncelli
B
K
author
2019
English
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.
Chance-constrained programming
Infeasible irreducible subsystems
Integer programming
WOS:000463792400003
exported from refbase (http://ficpubs.uai.cl/show.php?record=996), last updated on Thu, 02 Jan 2020 17:48:36 +0000
text
http://ficpubs.uai.cl/files/996_Canessa_etal2019.pdf
10.1007/s10589-018-00055-9
Canessa_etal2019
Computational Optimization And Applications
Comput. Optim. Appl.
2019
Springer
continuing
periodical
academic journal
72
3
589
608
0926-6003