线性加权gbest制导人工蜂群算法

Yanyu Zhang, P. Zeng, Yang Wang, Baohui Zhu, Fangjun Kuang
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引用次数: 7

摘要

人工蜂群(Artificial bee colony, ABC)算法是Karaboga最近提出的一种基于竞争随机种群的优化算法。然而,原始ABC算法中使用的解搜索方程具有较强的探索性和较差的开发性。为了改进ABC算法的利用,研究者提出了一种改进的ABC算法GABC (best-guided ABC, GABC)。为了进一步改进GABC算法,提出了一种具有线性权值的改进GABC算法WGABC,并引入了一种新的用于WGABC算法侦察蜂阶段的解搜索方程。在一组数值基准函数上的实验结果表明,WGABC在大多数实验中都优于ABC和GABC算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Linear Weighted Gbest-Guided Artificial Bee Colony Algorithm
Artificial bee colony (ABC) algorithm invented recently by Karaboga is a competitive stochastic population-based optimization algorithm. However, solution search equation used in the original ABC algorithm is good at exploration but poor at exploitation. an improved ABC algorithm called Gbest-guided ABC (GABC) was introduced by researchers to improve the exploitation of ABC algorithm. in order to improve the GABC algorithm further, we propose an improved GABC algorithm with a linear weight called WGABC, and introduce a novel solution search equation used at scout bee stage of WGABC algorithm. Experimental results tested on a set of numerical benchmark functions show that WGABC can outperform ABC and GABC algorithms in most of the experiments.
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