D-MAENS2: A Self-adaptive D-MAENS Algorithm with Better Decision Diversity

Qingquan Zhang, Feng Wu, Yang Tao, Jiyuan Pei, Jialin Liu, X. Yao
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引用次数: 1

Abstract

The capacitated arc routing problem is a challenging combinatorial optimization problem with numerous real-world applications. In recent years, several multi-objective optimization algorithms have been applied to minimize both the total cost and makespan for capacitated arc routing problems, among which the decomposition-based memetic algorithm with extended neighborhood search has shown promising results. In this paper, we propose an improved decomposition-based memetic algorithm with extended neighborhood search, called D-MAENS2, which uses a novel method to construct a gene pool to measure and improve the diversity of solutions in decision variable space. Additionally, D-MAENS2 is capable of adapting online its hyper-parameters to various problem instances. Experimental studies show that our novel D-MAENS2 significantly outperforms D-MAENS on 81 benchmark instances and shows outstanding performance on instances of large size.
D-MAENS2:一种具有更好决策多样性的自适应D-MAENS算法
电容电弧布线问题是一个具有挑战性的组合优化问题,具有许多实际应用。近年来,为了使电容电弧布线问题的总成本和最大完工时间同时最小化,已经应用了几种多目标优化算法,其中基于分解的扩展邻域搜索模因算法取得了良好的效果。本文提出了一种改进的基于分解的扩展邻域搜索模因算法D-MAENS2,该算法采用一种新颖的方法构建一个基因库来测量和提高决策变量空间中解的多样性。此外,D-MAENS2能够在线调整其超参数以适应各种问题实例。实验研究表明,我们的新型D-MAENS2在81个基准实例上显著优于D-MAENS,并且在大尺寸实例上表现出出色的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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