Abstract
As an evolutionary approach to solve multi-objective optimization problems involving several constraints, recently a MOEA using the two-stage non-dominated sorting and the directed mating (TNSDM) has been proposed. In TNSDM, the directed mating utilizes infeasible solutions dominating feasible solutions in the objective space to generate offspring. Our previous work showed that the directed mating significantly contributed to improve the search performance of TNSDM on several benchmark problems. However, the conventional directed mating has two problems. First, since the conventional directed mating selects a pair of parents based on the conventional Pareto dominance, two parents having different search directions are mated in some cases. Second, in problems with high feasibility ratio, since the number of infeasible solutions in the population is low, sometimes the directed mating cannot be performed. Consequently, the effectiveness of the directed mating cannot be obtained. To overcome these problems and further improve the effectiveness of the directed mating in TNSDM, in this work we propose a method to control selection areas of infeasible solutions by controlling dominance area of solutions (CDAS). We verify the effectiveness of the proposed method in TNSDM, and compare its search performance with the conventional CNSGA-II on \(m\) objectives \(k\) knapsacks problems. As results, we show that the search performance of TNSDM is further improved by controlling selection area of infeasible solutions in the directed mating.
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Miyakawa, M., Takadama, K., Sato, H. (2014). Controlling Selection Area of Useful Infeasible Solutions in Directed Mating for Evolutionary Constrained Multiobjective Optimization. In: Pardalos, P., Resende, M., Vogiatzis, C., Walteros, J. (eds) Learning and Intelligent Optimization. LION 2014. Lecture Notes in Computer Science(), vol 8426. Springer, Cham. https://doi.org/10.1007/978-3-319-09584-4_14
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