An approach for solving a fuzzy multiobjective programming problem

被引：42

作者：

Luhandjula, M. K. ^{[1
]}

Rangoaga, M. J. ^{[1
]}

机构：

[1] Univ S Africa, Dept Decis Sci, ZA-0003 Unisa, South Africa

来源：

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH | 2014年 / 232卷 / 02期

关键词：

Multiobjective programming; Fuzzy numbers; Nearest interval approximation; Pareto optimality; KKT conditions; gH-differentiability; OPTIMIZATION;

D O I：

10.1016/j.ejor.2013.05.040

中图分类号：

C93 [管理学];

学科分类号：

120117 [社会管理工程];

摘要：

In this paper we present a new approach, based on the Nearest Interval Approximation Operator, for dealing with a multiobjective programming problem with fuzzy-valued objective functions. By the way we have established a Karush-Kuhn-Tucker (K.K.T) kind of Pareto optimality conditions, for the resulting interval multiobjective program. To this end, we made use of gH-differentiability of involved interval-valued functions. Two algorithms play a pivotal role in the proposed method. The first one returns a nearest interval approximation to a given fuzzy number. The other one makes use of K.K.T conditions to deliver a Pareto optimal solution of the above mentioned resulting interval program. (c) 2013 Elsevier B.V. All rights reserved.

引用

页码：249 / 255

页数：7