JACIII Vol.18 No.2 pp. 221-231
doi: 10.20965/jaciii.2014.p0221


Archive of Useful Solutions for Directed Mating in Evolutionary Constrained Multiobjective Optimization

Minami Miyakawa, Keiki Takadama, and Hiroyuki Sato

The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan

October 15, 2013
January 31, 2014
March 20, 2014
evolutionary multi-objective optimization, constraint-handling, archive of solutions, directed mating
As an evolutionary approach to solve multi-objective optimization problems involving several constraints, recently a multi-objective evolutionary algorithm (MOEA) using two-stage non-dominated sorting and directed mating (TNSDM) has been proposed. In TNSDM, directed mating utilizes infeasible solutions dominating feasible solutions in the objective space to generate offspring. In our previous studies, significant contribution of directed mating to the improvement of the search performancewas verified on several benchmark problems. However, in the conventional TNSDM, infeasible solutions utilized in directed mating are discarded in the selection process of parents (elites) population and cannot be utilized in the next generation. TNSDM has potential to further improve the search performance by archiving useful solutions for directed mating to the next generation and repeatedly utilizing them in directed mating. To further improve effects of directed mating in TNSDM, in this work, we propose an archiving strategy of useful solutions for directed mating. We verify the search performance of TNSDM using the proposed archive by varying the size of archive, and compare its search performance with the conventional CNSGA-II and RTS on m objectives k knapsacks problems. As results, we show that the search performance of TNSDM is improved by introducing the proposed archive in aspects of diversity of the obtained solutions in the objective space and convergence of solutions toward the optimal Pareto front.
Cite this article as:
M. Miyakawa, K. Takadama, and H. Sato, “Archive of Useful Solutions for Directed Mating in Evolutionary Constrained Multiobjective Optimization,” J. Adv. Comput. Intell. Intell. Inform., Vol.18 No.2, pp. 221-231, 2014.
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