This paper proposes a new parent selection method for reducing the effect of evaluation time bias in asynchronous parallel evolutionary algorithms (APEAs). APEAs have the advantage of increasing computational efficiency even when the evaluation times of solutions differ. However, APEAs have a problem that their search direction is biased toward the search region with a short evaluation time. The proposed parent selection method considers the search frequency of solutions to reduce such an adverse influence of APEAs while maintaining their computational efficiency. We conduct experiments on toy problems that reproduce the evaluation time bias on multi-objective optimization problems to investigate the effectiveness of the proposed method. The experiments use NSGA-III, a well-known multi-objective evolutionary algorithm. In the experiments, we compare the proposed method with the synchronous and asynchronous methods. The experimental results reveal that the proposed method can reduce the effect of the evaluation time bias while reducing the computing time of the parallel NSGA-III.

中文翻译：

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用于减少异步并行多目标进化算法中评估时间偏差影响的基于频率的父选择

本文提出了一种新的父选择方法，用于减少异步并行进化算法 (APEA) 中评估时间偏差的影响。即使解决方案的评估时间不同，APEA 也具有提高计算效率的优势。然而，APEAs 存在一个问题，即它们的搜索方向偏向于评估时间较短的搜索区域。提议的父选择方法考虑了解决方案的搜索频率，以减少 APEA 的这种不利影响，同时保持其计算效率。我们对重现多目标优化问题的评估时间偏差的玩具问题进行了实验，以研究所提出方法的有效性。实验使用了著名的多目标进化算法 NSGA-III。在实验中，我们将所提出的方法与同步和异步方法进行比较。实验结果表明，所提出的方法在减少并行NSGA-III的计算时间的同时，可以减少评估时间偏差的影响。