Title
Tight Second Stage Formulations in Two-Stage Stochastic Mixed Integer Programs.
Abstract
We study two-stage stochastic mixed integer programs (TSS-MIPs) with integer variables in the second stage. We show that under suitable conditions, the second stage MIPs can be convexified by adding parametric cuts a priori. As special cases, we extend the results of Miller and Wolsey [Math. Program., 98 (2003), pp. 73-88] to TSS-MIPs. Furthermore, we consider second stage programs that are generalizations of the well-known mixing (and continuous mixing) set, or certain piecewise-linear convex objective integer programs. These results allow us to relax the integrality restrictions on the second stage integer variables without effecting the integrality of the optimal solution of the TSS-MIP. We also use four variants of the two-stage stochastic capacitated lot-sizing problems as test problems for computational experiments and present tight second stage formulations for these problems. Our computational results show that adding parametric inequalities that a priori convexify the second stage formulation significantly reduces the total solution time taken to solve these problems.
Year
DOI
Venue
2018
10.1137/16M1083955
SIAM JOURNAL ON OPTIMIZATION
Keywords
Field
DocType
two-stage stochastic mixed integer program,tight extended formulation,convex hull,parametric cuts,continuous multi-mixing set,capacitated lot-sizing with backlogging,discrete lot-sizing
Integer,Discrete mathematics,Mathematical optimization,Generalization,A priori and a posteriori,Convex hull,Regular polygon,Parametric statistics,Mathematics
Journal
Volume
Issue
ISSN
28
1
1052-6234
Citations 
PageRank 
References 
1
0.36
18
Authors
3
Name
Order
Citations
PageRank
Manish Bansal152.80
Kuo-Ling Huang2804.95
Sanjay Mehrotra352177.18