Orbital shrinking: Theory and applications

被引:2
作者
Fischetti, Matteo [1 ]
Liberti, Leo [2 ]
Salvagnin, Domenico [1 ]
Walsh, Toby [3 ,4 ]
机构
[1] Univ Padua, DEI, Padua, Italy
[2] Ecole Polytech, CNRS LIX, F-91128 Palaiseau, France
[3] NICTA, Sydney, NSW, Australia
[4] UNSW, Sydney, NSW, Australia
关键词
Mathematical programming; Constraint programming; Discrete optimization; Symmetry; Relaxation; MINLP; SYMMETRY; CONSTRAINT; BOUNDS;
D O I
10.1016/j.dam.2017.01.015
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We present a method, based on formulation symmetry, for generating Mixed-Integer Linear Programming (MILP) relaxations with fewer variables than the original symmetric MILP. Our technique also extends to convex MINLP, and some nonconvex MINLP with a special structure. We showcase the effectiveness of our relaxation when embedded in a decomposition method applied to two important applications (multi-activity shift scheduling and multiple knapsack problem), showing that it can improve CPU times by several orders of magnitude compared to pure MIP or CP approaches. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:109 / 123
页数:15
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