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一种结合和声搜索的有效萤火虫算法用于全局数值优化。

An effective hybrid firefly algorithm with harmony search for global numerical optimization.

作者信息

Guo Lihong, Wang Gai-Ge, Wang Heqi, Wang Dinan

机构信息

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.

School of Computer Science and Technology, Jiangsu Normal University, Xuzhou, Jiangsu 221116, China.

出版信息

ScientificWorldJournal. 2013 Nov 20;2013:125625. doi: 10.1155/2013/125625. eCollection 2013.

DOI:10.1155/2013/125625
PMID:24348137
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3856164/
Abstract

A hybrid metaheuristic approach by hybridizing harmony search (HS) and firefly algorithm (FA), namely, HS/FA, is proposed to solve function optimization. In HS/FA, the exploration of HS and the exploitation of FA are fully exerted, so HS/FA has a faster convergence speed than HS and FA. Also, top fireflies scheme is introduced to reduce running time, and HS is utilized to mutate between fireflies when updating fireflies. The HS/FA method is verified by various benchmarks. From the experiments, the implementation of HS/FA is better than the standard FA and other eight optimization methods.

摘要

提出了一种将和声搜索（HS）和萤火虫算法（FA）相结合的混合元启发式方法，即HS/FA，用于解决函数优化问题。在HS/FA中，充分发挥了HS的探索能力和FA的利用能力，因此HS/FA比HS和FA具有更快的收敛速度。此外，引入了顶级萤火虫方案以减少运行时间，并在更新萤火虫时利用HS在萤火虫之间进行变异。HS/FA方法通过各种基准进行了验证。从实验结果来看，HS/FA的实现效果优于标准FA和其他八种优化方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/071b/3856164/d375365a48f4/TSWJ2013-125625.alg.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/071b/3856164/801301fa8152/TSWJ2013-125625.001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/071b/3856164/5d2c52c22d6c/TSWJ2013-125625.alg.001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/071b/3856164/d375365a48f4/TSWJ2013-125625.alg.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/071b/3856164/801301fa8152/TSWJ2013-125625.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/071b/3856164/6e120c3af93b/TSWJ2013-125625.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/071b/3856164/20861aaed340/TSWJ2013-125625.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/071b/3856164/e41f903a7327/TSWJ2013-125625.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/071b/3856164/5d2c52c22d6c/TSWJ2013-125625.alg.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/071b/3856164/32b5dfcfebe7/TSWJ2013-125625.alg.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/071b/3856164/d375365a48f4/TSWJ2013-125625.alg.003.jpg

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