Intuitionistic fuzzy optimization technique for solving multi-objective reliability optimization problems in interval environment |
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| Affiliation: | 1. School of Mathematics and Computer Applications, Thapar University, Patiala 147004, Punjab, India;2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India;1. Department of Information Management at Fortune Institute of Technology, Kaohsiung, Taiwan;2. Thecus Technology Corporation, Taiwan;3. Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan;1. Chongqing Key Lab of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing, China;2. Graduate Telecommunications and Networking Program, University of Pittsburgh, PA, USA;3. China Internet Research Lab, China Science and Technology Network, Computer Network Information Center, Chinese Academy of Sciences, Beijing, China;4. Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China;1. Department of International Trade, Jinwen University of Science and Technology, No. 99, Anzhong Rd., Xindian Dist., New Taipei City 23154, Taiwan;2. Department of Industrial Management, Lunghwa University of Science and Technology, No. 300, Sec. 1, Wanshou Rd., Guishan Shiang, Taoyuan County 33306, Taiwan;3. Department of Industrial Management and Enterprise Information, Aletheia University, 32, Chen-Li Street, Tamsui, New Taipei City 251, Taiwan;1. College of Computer Science, Zhejiang University, Hangzhou 310027, China;2. School of Information Systems, Singapore Management University, Singapore 178902, Singapore |
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| Abstract: | 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. |
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| Keywords: | Multi-objective optimization PSO Reliability optimization Intuitionistic fuzzy set theory Membership functions |
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