Title
Using DRL* relaxations for quadratically constrained pseudoboolean optimization: application to robust Min-Cut
Abstract
In this work we focus on solving quadratically constrained pseudoboolean optimization problems with quadratic objective as mixed integer linear programs. The standard mixed integer linear formulation of such problems is strengthened using valid inequalities derived from solving Reformulation-Linearization relaxation called partial DRL* relaxation. The proposed PDRL* relaxation features block-decomposable structure which are exploited to improve computational efficiency. We present computational results obtained with the rank 2 PDRL*, showing that the proposed mixed integer linear formulation gives rise to significant reduction factors (typically more than 1000) in the size of the branch and bound trees on instances of robust minimum cut problem with weight constraints.
Year
DOI
Venue
2010
10.1016/j.endm.2010.05.154
Electronic Notes in Discrete Mathematics
Keywords
Field
DocType
mixed integer programming,robust optimization,rlt,branch and bound,optimization problem,minimum cut
Discrete mathematics,Mathematical optimization,Combinatorics,Quadratically constrained quadratic program,Branch and cut,Branch and price,Minimum cut,Integer programming,Linear programming relaxation,Optimization problem,Mathematics,Special ordered set
Journal
Volume
ISSN
Citations 
36
Electronic Notes in Discrete Mathematics
0
PageRank 
References 
Authors
0.34
6
2
Name
Order
Citations
PageRank
Michel Minoux1741100.18
Hacene Ouzia2181.69