10th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)

Research Article

Polynomial Mean-Centric Crossover for Directed Mating in Evolutionary Constrained Multi-Objective Continuous Optimization

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  • @INPROCEEDINGS{10.4108/eai.22-3-2017.152401,
        author={Minami Miyakawa and Hiroyuki Sato and Yuji Sato},
        title={Polynomial Mean-Centric Crossover for Directed Mating in Evolutionary Constrained Multi-Objective Continuous Optimization},
        proceedings={10th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)},
        publisher={EAI},
        proceedings_a={BICT},
        year={2017},
        month={3},
        keywords={constrained multi-objective optimization evolutionary algorithms utilization of infeasible solutions crossover operetor},
        doi={10.4108/eai.22-3-2017.152401}
    }
    
  • Minami Miyakawa
    Hiroyuki Sato
    Yuji Sato
    Year: 2017
    Polynomial Mean-Centric Crossover for Directed Mating in Evolutionary Constrained Multi-Objective Continuous Optimization
    BICT
    EAI
    DOI: 10.4108/eai.22-3-2017.152401
Minami Miyakawa1,*, Hiroyuki Sato2, Yuji Sato3
  • 1: JSPS Research Fellow (PD), Hosei University
  • 2: The University of Electro-Communications
  • 3: Hosei University
*Contact email: miyakawa@cis.k.hosei.ac.jp

Abstract

This paper proposes a mean-centric crossover to improve the effectiveness of the directed mating utilizing useful infeasible solutions in evolutionary constrained multi-objective continuous optimization. The directed mating selects a feasible solution as the first parent and a solution dominating the first parent in the objective space from the population involving infeasible solutions as the second parent. Since infeasible solutions having better objective values than feasible ones have useful variables, it helps to improve the search performance. So far, the commonly used simulated binary crossover (SBX) have been employed to generate offspring from two parents selected by the directed mating. However, it is not clear that the commonly used SBX is appropriate also for parents selected by the directed mating. When the Pareto front exists on the boundary between the feasible and the infeasible regions in the variable space, a mean-centric crossover generating offspring around intermediate area of two parents would be more effective than SBX which is a parent-centric crossover generating offspring around two parents. This work proposes the polynomial mean-centric crossover (PMCX) and combines it with the directed mating. The experimental results show that the proposed PMCX achieves higher search performance than SBX on several test problems.