Global Optimization of a Class of Nonconvex Quadratically Constrained Quadratic Programming Problems

作     者：Yong XIA 

作者机构：LMIB of the Ministry of Education School of Mathematics and Systems Science Beihang University Beijing 100191 P. R. China 

出 版 物：《Acta Mathematica Sinica,English Series》 (数学学报（英文版）)

年 卷 期：2011年第27卷第9期

页      面：1803-1812页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0701[理学-数学] 

基　　金：Supported by the fundamental research funds for the central universities under grant YWF-10-02-021 and by National Natural Science Foundation of China under grant 11001006 The author is very grateful to all the three anonymous referees for their constructive criticisms and useful suggestions that help to improve the paper 

主　　题：Nonconvex programming quadratically constrained quadratic programming quadratic assignment problem polynomial solvability strong duality 

摘      要：In this paper we study a Class of nonconvex quadratically constrained quadratic programming problems generalized from relaxations of quadratic assignment problems. We show that each problem is polynomially solved. Strong duality holds if a redundant constraint is introduced. As an application, a new lower bound is proposed for the quadratic assignment problem.