Global optimality conditions and optimization methods for constrained polynomial programming problems

被引：2
作者：
Wu, Zhiyou [1 ,2 ]
Tian, Jing [2 ]
Ugon, Julien [2 ]
Zhang, Liang [1 ]
机构：
[1] Chongqing Normal Univ, Sch Math Sci, Chongqing 401331, Peoples R China
[2] Federat Univ Australia, Sch Sci Informat Technol & Engn, Ballarat, Vic 3353, Australia
来源：
APPLIED MATHEMATICS AND COMPUTATION | 2015年 / 262卷
关键词：
Constrained polynomial programming; Problem; Necessary global optimality condition; Linear transformation; Local optimization method; Global optimization method; UNIVARIATE; MINIMIZATION; RELAXATIONS; ALGORITHM;
D O I：
10.1016/j.amc.2015.04.040
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The general constrained polynomial programming problem (GPP) is considered in this paper. Problem (GPP) has a broad range of applications and is proved to be NP-hard. Necessary global optimality conditions for problem (GPP) are established. Then, a new local optimization method for this problem is proposed by exploiting these necessary global optimality conditions. A global optimization method is proposed for this problem by combining this local optimization method together with an auxiliary function. Some numerical examples are also given to illustrate that these approaches are very efficient. (C) 2015 Elsevier Inc. All rights reserved.
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页码：312 / 325
页数：14
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