A Niching Indicator-Based Multi-modal Many-objective Optimizer

• URL: http://arxiv.org/abs/2010.00236v1
• Date: Thu, 1 Oct 2020 07:45:46 GMT
• Title: A Niching Indicator-Based Multi-modal Many-objective Optimizer
• Authors: Ryoji Tanabe and Hisao Ishibuchi
• Abstract summary: There is no efficient method for multi-modal many-objective optimization, where the number of objectives is more than three. This paper proposes a niching indicator-based multi-modal multi- and many-objective optimization algorithm.
• Score: 7.81768535871051
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Multi-modal multi-objective optimization is to locate (almost) equivalent Pareto optimal solutions as many as possible. Some evolutionary algorithms for multi-modal multi-objective optimization have been proposed in the literature. However, there is no efficient method for multi-modal many-objective optimization, where the number of objectives is more than three. To address this issue, this paper proposes a niching indicator-based multi-modal multi- and many-objective optimization algorithm. In the proposed method, the fitness calculation is performed among a child and its closest individuals in the solution space to maintain the diversity. The performance of the proposed method is evaluated on multi-modal multi-objective test problems with up to 15 objectives. Results show that the proposed method can handle a large number of objectives and find a good approximation of multiple equivalent Pareto optimal solutions. The results also show that the proposed method performs significantly better than eight multi-objective evolutionary algorithms.

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