Fuzzy linear optimization in the presence of the fuzzy relation inequality constraints with max–min composition

In this paper, we study the new linear objective function optimization with respect to the fuzzy relational inequalities defined by max–min composition in which fuzzy inequality replaces ordinary inequality in the constraints. Fuzzy inequalities enable us to attain the optimal points that are better...

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Bibliographic Details
Published in:	Information sciences Vol. 178; no. 2; pp. 501 - 519
Main Authors:	Ghodousian, A., Khorram, E.
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 15.01.2008
Subjects:	Fuzzy compositions Fuzzy relational equalities Fuzzy relational inequalities Linear objective function optimization T-norms Fuzzy relational inequalities T-norms Fuzzy relational equalities Fuzzy compositions Linear objective function optimization
ISSN:	0020-0255, 1872-6291
Online Access:	Get full text
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Summary:	In this paper, we study the new linear objective function optimization with respect to the fuzzy relational inequalities defined by max–min composition in which fuzzy inequality replaces ordinary inequality in the constraints. Fuzzy inequalities enable us to attain the optimal points that are better solutions than those resulting from the resolution of the similar problems with Ordinary Inequality constraints (denoted by x OI in this paper). We have presented an algorithm to generate such optimal solutions. Also two examples are given to illustrate the algorithm presented and some real application of this work.
ISSN:	0020-0255 1872-6291
DOI:	10.1016/j.ins.2007.07.022