| 仿生策略优化的鲸鱼算法研究 |
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| 引用本文： | 巩世兵,沈海斌. 仿生策略优化的鲸鱼算法研究[J]. 传感器与微系统, 2017, 0(12): 10-12. DOI: 10.13873/J.1000-9787(2017)12-0010-03 |
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| 作者姓名： | 巩世兵 沈海斌 |
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| 作者单位： | 浙江大学超大规模集成电路设计研究所,浙江杭州,310027 |
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| 基金项目： | 国家“863”计划资助项目 |
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| 摘 要： | 通过对混沌映射初始化种群和自适应调整搜索策略对鲸鱼优化算法(WOA)改进,提出了仿生策略优化的鲸鱼算法(BWOA),实现了对算法的全局优化能力和收敛速度的改进.通过基准测试函数的仿真,BWOA与标准WOA及高效的WOA(EWOA)对比分析,证明了BWOA的有效性.
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| 关 键 词： | 鲸鱼算法 仿生策略 群智优化算法 切比雪夫序列 混沌映射初始化种群 |
Study of whale algorithm for biomimetic strategy optimization |
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| Abstract: | The whale optimization algorithm(WOA) is inspired by the hunting behavior of humpback whales and it's presented as a new swarm-based optimization algorithm recently.This study proposes an improved whale optimization algorithm with optimization strategy of bionics (BWOA)by Chaos mapping initialization population and adaptive adjusting search strategy,in order to improve the accuracy of global optimization and the rate of convergence.By simulation on reference test function,BWOA is compared with standard WOA and effective WOA (EWOA),efficiency of BWOA,is demonstrated. |
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| Keywords: | whale optimization algorithm (WOA) biomimetic strategy swarm-based optimization algorithm Chebyshev sequences initial population based on Chaos mapping |
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