DECOMPOSITION BRANCH-AND-BOUND METHOD FOR GLOBALLY SOLVING LINEARLY CONSTRAINED INDEFINITE QUADRATIC MINIMIZATION PROBLEMS

被引：30

作者：

PHONG, TQ

AN, LTH

TAO, PD

机构：

[1] LMI-INSA Rouen, 76131 Mont Saint Aignan Cedex, Place Emile Blondel

来源：

OPERATIONS RESEARCH LETTERS | 1995年 / 17卷 / 05期

关键词：

GLOBAL MINIMIZATION; INDEFINITE QUADRATIC PROGRAMMING; DECOMPOSITION; BRANCH AND BOUND;

D O I：

10.1016/0167-6377(95)00014-B

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

A decomposition branch and bound approach is considered for the global minimization of an indefinite quadratic function over a polytope. The objective function is a sum of a nonseparable convex part and a separable concave part. In many large-scale problems the number of convex variables is much larger than that of concave variables. Taking advantage of this we use a branch and bound method where branching proceeds by rectangular subdivision of the subspace of concave variables. With the help of an easily constructed convex underestimator of the objective function, a lower bound is obtained by solving a convex quadratic programming problem. Three variants using exhaustive, adaptive and w-subdivision are discussed. Computational results are presented for problems with 10-20 concave variables and up to 200 convex variables.

引用

页码：215 / 220

页数：6

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