Parameter tuning for ant colony optimization: A review

K. Wong, Komarudin
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引用次数: 34

Abstract

Ant Colony Optimization (ACO) has enjoyed development and improvement since it was introduced in 1990s. The development of ACO was primarily driven by its convergence problem. Balancing between intensification and diversification in the search space is an important factor to intelligently improve solutions and avoid premature convergence. Balancing intensification and diversification can be gained by controlling the parameters value (this is called parameter tuning). Unfortunately, only little research has been reported to adopt parameter tuning as a strategy to balance intensification and diversification in ACO. This paper review parameter tuning in ACO published in the literature.
蚁群优化的参数调整:综述
蚁群算法自20世纪90年代提出以来,得到了不断的发展和完善。蚁群算法的发展主要受到其收敛性问题的推动。平衡搜索空间的集约化和多样化是智能改进解决方案和避免过早收敛的重要因素。可以通过控制参数值(这称为参数调优)来平衡强化和多样化。不幸的是,只有很少的研究报告采用参数调整作为策略来平衡集约化和多样化的蚁群控制。本文对已发表的蚁群算法的参数整定进行了综述。
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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