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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Vydáno v:Information sciences Ročník 178; číslo 2; s. 501 - 519
Hlavní autoři: Ghodousian, A., Khorram, E.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Inc 15.01.2008
Témata:
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
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Shrnutí: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