An Outcome Space Branch-and-Bound Algorithm for a Class of Linear Multiplicative Programming Problems

被引：0

作者：

Gao, Yuelin ^{[1
,2
]}

Zhang, Nihong ^{[1
]}

Ma, Xiaohua ^{[1
]}

机构：

[1] Beifang Univ Nationalities, Inst Informat & Syst Sci, Yinchuan 750021, Peoples R China

[2] Ningxia Univ, Sch Math & Comp Sci, Yinchuan 750021, Peoples R China

来源：

ADVANCES IN GLOBAL OPTIMIZATION | 2015年 / 95卷

关键词：

Global optimization; Linear multiplicative programming; Branch-and-bound; Outcome space; GLOBAL OPTIMIZATION; SET;

D O I：

10.1007/978-3-319-08377-3_5

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

This article presents an outcome space branch-and-bound algorithm for globally solving a class of linear multiplicative programming problem. In this algorithm, the lower bound is found by solving a separable relaxation programming problem. A convex quadratic programming problem is constructed so as to improve the ability to set the upper bound. The convergence of the algorithm is proved. Numerical experiments are reported to show the feasibility and effectiveness of the proposed algorithm.

引用

页码：40 / 49

页数：10

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