Self-adaptive step glowworm swarm optimization algorithm

doi:10.3724/SP.J.1087.2011.01804

Journal of Computer Applications ›› 2011, Vol. 31 ›› Issue (07): 1804-1807.DOI: 10.3724/SP.J.1087.2011.01804

• Network and distributed techno • Previous Articles Next Articles

Self-adaptive step glowworm swarm optimization algorithm

Zhe OUYANG,Yong-quan ZHOU

College of Mathematics and Computer Science,Guangxi University for Nationalities,Nanning Guangxi 530006,China

Received:2011-01-04 Revised:2011-02-24 Online:2011-07-01 Published:2011-07-01
Contact: Yong-quan ZHOU

自适应步长萤火虫优化算法

欧阳喆,周永权

广西民族大学数学与计算机科学学院，南宁 530006

通讯作者: 周永权
作者简介:欧阳喆(1988-),女,江西吉安人,硕士研究生,主要研究方向：智能计算;周永权（1962-）,男,陕西旬邑人,教授,博士,主要研究方向：神经网络、计算智能。
基金资助:
广西自然科学基金资助项目

Abstract

Abstract: According to the problem that Glowworm Swarm Optimization (GSO) cannot acquire solutions exactly and converge slowly in the later period for solving the multimodal function，an improved GSO algorithm combined with luciferinfactor, which can adaptively adjust step, was proposed. The simulation results show that the improved Self-Adaptive Step Glowworm Swarm Optimization (ASGSO) can search for global optimization more quickly and precisely.

Key words: multimodal function, Glowworm Swarm Optimization (GSO), self-adaptive, luciferin-factor

摘要： 针对基本萤火虫算法优化多峰函数时求解精度不高和后期收敛较慢的问题，引入萤光因子以自适应调整萤火虫的步长，提出一种自适应步长萤火虫优化算法。通过8个标准测试函数测试，测试结果表明，改进后的自适应步长萤火虫算法比基本萤火虫算法具有较快的寻优速度和较高的寻优精度。

关键词: 多峰函数, 萤火虫算法, 自适应, 萤光因子

CLC Number:

Zhe OUYANG Yong-quan ZHOU. Self-adaptive step glowworm swarm optimization algorithm[J]. Journal of Computer Applications, 2011, 31(07): 1804-1807.

欧阳喆周永权. 自适应步长萤火虫优化算法[J]. 计算机应用, 2011, 31(07): 1804-1807.

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Self-adaptive step glowworm swarm optimization algorithm

自适应步长萤火虫优化算法

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