A New Hybrid Intelligent Algorithm for Fuzzy Multiobjective Programming Problem Based on Credibility Theory

• Published in: Mathematical problems in engineering Vol. 2014; no. 2014; pp. 1 - 11
• Main Authors: Wang, Zu-Tong, Guo, Jian-Sheng, Zheng, Ming-Fa, Wang, Ying
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Puplishing Corporation 01.01.2014; Hindawi Publishing Corporation; Hindawi Limited
• Subjects: Algorithms; Design optimization; Expected values; Fuzzy; Fuzzy logic; Fuzzy set theory; Fuzzy systems; Hybrid systems; Hypercubes; Latin hypercube sampling; Mathematical models; Mathematical programming; Multiple objective; Multiple objective analysis; Optimization; Search algorithms; Support vector machines; Swarm intelligence; Systems design; Theory
• ISSN: 1024-123X; 1563-5147
• DOI: 10.1155/2014/909203

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, fuzzy simulation, support vector machine, and artificial bee colony algorithm are integrated to build a hybrid intelligent algorithm. An application case study on availability allocation optimization problem in repairable parallel-series system design is documented. The results suggest that the proposed method has excellent consistency and efficiency in solving fuzzy multiobjective programming problem and is particularly useful for expensive systems.