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Intuitionistic fuzzy optimization technique for solving multi-objective reliability optimization problems in interval environment
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DOI：10.1016/j.eswa.2013.11.014.png)
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Abstract
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In designing phase of systems, design parameters such as component reliabilities and cost are normally under uncertainties. This paper presents a methodology for solving the multi-objective reliability optimization model in which parameters are considered as imprecise in terms of triangular interval data. The uncertain multi-objective optimization model is converted into deterministic multi-objective model including left, center and right interval functions. A conflicting nature between the objectives is resolved with the help of intuitionistic fuzzy programming technique by considering linear as well as the nonlinear degree of membership and non-membership functions. The resultants max-min problem has been solved with particle swarm optimization (PSO) and compared their results with genetic algorithm (GA). Finally, a numerical instance is presented to show the performance of the proposed approach. (C) 2013 Elsevier Ltd. All rights reserved.
Keywords:
Multi-objective optimization
PSO
Reliability optimization
Intuitionistic fuzzy set theory
Membership functions
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