一种新的离散鳗鱼群智能算法

Sun Yao-sheng, Huang Zhang-can, Chen Yu, Yu-Te Chao
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摘要

本文受鳗鱼迁移行为的启发,提出了一种新的离散鳗鱼群智能算法。本文首先分析了鳗鱼的行为,然后建立了提取重要行为的数学模型。在合理组织鳗鲡集中适应、邻域学习和性别突变三种重要行为的基础上,提出了用于组合优化问题的离散鳗鲡群智能算法。最后,对TSP问题和置换流水车间调度问题进行了数值实验,结果表明该算法具有较强的优化能力和精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new discrete eel swarm intelligence algorithm
Inspired by the migration behaviours of eels, we propose a new discrete eel swarm intelligence algorithm in this paper. First, this paper analyzes the behaviours of eels, then establishes a mathematical model of the important behaviour being extracted. Based on rational organization of three important behaviours of eel, namely concentration adaptation, neighbourhood learning and gender mutation, the discrete eel swarm intelligence algorithm is proposed for combinatorial optimization problems. Finally, numerical experiments on the TSP problem and the permutation flow-shop scheduling problem show that the algorithm has strong optimization capability and accuracy.
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