探索元启发式算法中边界控制方法激活的频率

T. Kadavy, Michal Pluhacek, Adam Viktorin, R. Šenkeřík
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引用次数: 0

摘要

近年来,边界控制方法(bcm)在元启发式算法领域的应用越来越广泛。在本研究中,我们研究了不同脑卒中脑卒中的激活频率与问题维度之间的关系。此外,我们独立分析每个问题维度。我们的研究主要集中在IEEE CEC 2020竞赛中排名前三的算法:AGSK、IMODE和j2020,利用竞赛基准集进行实验。我们的发现为元启发式领域提供了有价值的见解,强调了理解BCM激活模式对改进算法设计和基准实践的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring the Frequency of Boundary Control Methods Activation in Metaheuristic Algorithms
Recently, Boundary Control Methods (BCMs) have become increasingly relevant in the field of metaheuristic algorithms. In this study, we investigate the relationship between the activation frequency of different BCMs and the problem's dimensionality. Additionally, we analyze each problem dimension independently. Our research primarily concentrates on the top three algorithms from the IEEE CEC 2020 competition: AGSK, IMODE, and j2020, utilizing the competition benchmark set to conduct experiments. Our findings provide valuable insights into the metaheuristic domain, underlining the significance of comprehending BCM activation patterns to improve algorithm design and benchmarking practices.
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