元超启发式框架下的解空间多样性管理

J. Grobler, A. Engelbrecht
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引用次数: 3

摘要

本文研究了在元超启发式算法背景下解决空间多样性管理的各种策略。提出了自适应局部搜索元超启发式算法(ALSHH),该算法在种群多样性偏离预定的解空间多样性轮廓时自适应地应用局部搜索算法。结果表明,ALSHH与在优化运行过程中以恒定间隔应用局部搜索和多样性维护策略的算法相比具有优势。对于另外两种流行的多方法算法也证明了良好的性能。
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Solution Space Diversity Management in a Meta-hyperheuristic Framework
This paper investigates various strategies for the management of solution space diversity within the context of a meta-hyper heuristic algorithm. The adaptive local search meta-hyper heuristic (ALSHH), which adaptively applies a local search algorithm when the population diversity strays outside a predetermined solution space diversity profile, is proposed. ALSHH was shown to compare favourably with algorithms making use of local search and diversity maintenance strategies applied at constant intervals throughout the optimization run. Good performance is also demonstrated with respect to two other popular multi-method algorithms.
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