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A Niching Multi-objective Harmony Search Algorithm for Multimodal Multi-objective Problems

机译:一种多模态多目标问题的小生多目标和谐搜索算法

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A modified multi-objective harmony search algorithm called Niching Multi-objective Harmony Search Algorithm (NMOHSA) is proposed to solve multimodal multi-objective optimization problems. It adopts the neighborhood information to build dynamic harmony memory for maintaining the population diversity. A new memory consideration rule is also applied to prevent the algorithm be trapped into local optimal solution. Moreover, two key parameters, harmony memory consideration rate (HMCR) and pitch adjustment rate (PAR), are dynamically adjusted. Empirical results show that the proposed algorithm performs much better than the other existing multimodal multi-objective algorithms in terms of the solution quality.
机译:为了解决多峰多目标优化问题,提出了一种改进的多目标和声搜索算法,称为Niching多目标和声搜索算法(NMOHSA)。它采用邻域信息来建立动态和谐记忆,以维持人口多样性。还应用了新的内存考虑规则,以防止算法陷入局部最优解中。而且,两个关键参数,和声记忆考虑率(HMCR)和音高调整率(PAR)被动态调整。实验结果表明,该算法在求解质量上比其他现有的多峰多目标算法有更好的表现。

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