.png){kind=icon}
返回
An approach for solving a fuzzy multiobjective programming problem
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ejor.2013.05.040.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
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.
Keyword:
Multiobjective programming
Fuzzy numbers
Nearest interval approximation
Pareto optimality
KKT conditions
gH-differentiability
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6
论文数:
2.2W
被引数:
6.4W
机构
引用论文
Photosynthetic oxygen evolution: Net charge transients as inferred from electrochromic bandshifts are independent of proton release into the medium.png)
FEBS Letters
OAAI
FEBS LettersIF0
OAAI分享收藏
查看更多内容