Abstract
This paper considers solving a multi-objective optimization problem with sup-T equation constraints. A set covering-based technique for order of preference by similarity to the ideal solution is proposed for solving such a problem. It is shown that a compromise solution of the sup-T equation constrained multi-objective optimization problem can be obtained by solving an associated set covering problem. A surrogate heuristic is then applied to solve the resulting optimization problem. Numerical experiments on solving randomly generated multi-objective optimization problems with sup-T equation constraints are included. Our computational results confirm the efficiency of the proposed method and show its potential for solving large scale sup-T equation constrained multi-objective optimization problems.
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Cheng-Feng Hu is currently with the Department of Applied Mathematics, National Chaiyi University, Taiwan, China. She received her BS degree from National Tsing Hua University in Taiwan, China and PhD degree from North Carolina State University in Raleigh, North Carolina, USA., in 1993 and 1997 respectively. Her research interests include Fuzzy Optimization and Decision Making, and Financial Engineering.
Shu-Cherng Fang holds the Walter Clark Chair Professorship and Alumni Distinguished Graduate Professorship at the North Carolina State University, USA. He received his PhD degree in industrial engineering and management science from Northwestern University located in Evanston, Illinois, USA. Professor Fang’s research interests include Linear and Nonlinear Programming, Fuzzy Optimization and Decision Making, Soft Computing, Logistics and Supply Chain Management. He has published over 200 research articles and served on 20 plus editorial boards. He is the current Editor-in-Chief of Fuzzy Optimization and Decision Making.
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Hu, CF., Fang, SC. Set covering-based topsis method for sloving sup-T equation constrained multi-objective optimization problems. J. Syst. Sci. Syst. Eng. 24, 258–275 (2015). https://doi.org/10.1007/s11518-014-5261-x
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DOI: https://doi.org/10.1007/s11518-014-5261-x