A New Hybrid Intelligent Algorithm for Fuzzy Multiobjective Programming Problem Based on Credibility Theory
Author(s) -
Zutong Wang,
Jiansheng Guo,
Mingfa Zheng,
Ying Wang
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/909203
Subject(s) - credibility theory , mathematical optimization , fuzzy logic , latin hypercube sampling , credibility , computer science , basis (linear algebra) , fuzzy transportation , fuzzy set operations , fuzzy set , mathematics , artificial intelligence , monte carlo method , statistics , geometry , law , political science
Based on the credibility theory, this paper is devoted to the fuzzy multiobjective programming problem. Firstly,the expected-value model of fuzzy multiobjective programming problem is provided based on credibility theory;then two new approaches for obtaining efficient solutions are proposed on the basis of the expected-value model,whose validity has been proven. For solving the fuzzy MOP problem efficiently, Latin hypercube sampling, fuzzysimulation, support vector machine, and artificial bee colony algorithm are integrated to build a hybrid intelligentalgorithm. An application case study on availability allocation optimization problem in repairable parallel-seriessystem design is documented. The results suggest that the proposed method has excellent consistency and efficiencyin solving fuzzy multiobjective programming problem and is particularly useful for expensive systems
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