Abstract
This study presents a multiple objective optimization problem with the solution space designed by a system of fuzzy relational equations based on max-product algebraic composition. The solution set of the fuzzy relation equation is generally characterized by a unique maximal solution and finite number of minimal solutions and is non-convex by nature. Owing to the nature of feasible space, the traditional metaheuristics cannot be applied in their original form. To overcome this situation, a modified version of NSGA-II has been presented. The original NSGA-II has set standards in the area of multiobjective optimization in terms of efficiency. But in our case, the algorithm fails to give feasible solutions at the end. For this, the algorithm is modified to adapt the algorithm in our problem domain. The whole procedure is illustrated by some test problems.
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Authors are thankful to referees for their valuable suggestions.
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Singh, G., Pandey, D., Thapar, A. (2015). A Modified NSGA-II for Fuzzy Relational Multiobjective Optimization Problem. In: Vijay, V., Yadav, S., Adhikari, B., Seshadri, H., Fulwani, D. (eds) Systems Thinking Approach for Social Problems. Lecture Notes in Electrical Engineering, vol 327. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2141-8_4
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