A practicable branch-and-bound algorithm for globally solving linear multiplicative programming

被引：44

作者：

Wang, Chun-Feng ^{[1
,2
]}

Bai, Yan-Qin ^{[1
]}

Shen, Pei-Ping ^{[2
]}

机构：

[1] Shanghai Univ, Dept Math, Shanghai, Peoples R China

[2] Henan Normal Univ, Dept Math, Xinxiang, Peoples R China

来源：

OPTIMIZATION | 2017年 / 66卷 / 03期

关键词：

Linear multiplicative; branch-and-bound; linear relaxation; global optimization; OPTIMIZATION; MINIMIZATION; EXPONENT;

D O I：

10.1080/02331934.2016.1269765

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：

To globally solve linear multiplicative programming problem (LMP), this paper presents a practicable branch-and-bound method based on the framework of branch-and-bound algorithm. In this method, a new linear relaxation technique is proposed firstly. Then, the branch-and-bound algorithm is developed for solving problem LMP. The proposed algorithm is proven that it is convergent to the global minimum by means of the subsequent solutions of a series of linear programming problems. Some experiments are reported to show the feasibility and efficiency of this algorithm.

引用

页码：397 / 405

页数：9