On the Newton method for solving fuzzy optimization problems

被引：40

作者：

Chalco-Cano, Y. ^{[1
]}

Silva, G. N. ^{[2
]}

Rufian-Lizana, A. ^{[1
,3
]}

机构：

[1] Univ Tarapaca, Inst Alta Invest, Arica, Chile

[2] UNESP, Inst Biociencias Letras & Ciencias Exatas, Dept Matemat Aplicada, Sao Jose Do Rio Preto, SP, Brazil

[3] Univ Seville, Dept Estadist & IO, Seville, Spain

来源：

FUZZY SETS AND SYSTEMS | 2015年 / 272卷

基金：

巴西圣保罗研究基金会;

关键词：

Fuzzy optimization; Generalized Hukuhara differentiability; Newton method; MATHEMATICAL-PROGRAMMING PROBLEMS; TUCKER OPTIMALITY CONDITIONS; VALUED OBJECTIVE FUNCTIONS; DIFFERENTIAL-EQUATIONS; MAPPINGS; CONVEX; INTERVAL; INEQUALITY;

D O I：

10.1016/j.fss.2015.02.001

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this article we consider optimization problems where the objectives are fuzzy functions (fuzzy-valued functions). For this class of fuzzy optimization problems we discuss the Newton method to find a non-dominated solution. For this purpose, we use the generalized Hukuhara differentiability notion, which is the most general concept of existing differentiability for fuzzy functions. This work improves and corrects the Newton method previously proposed in the literature. (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：60 / 69

页数：10

共 35 条

[1] Generalizations of the differentiability of fuzzy-number-valued functions with applications to fuzzy differential equations [J].