一种线性递减趋化步长的细菌觅食优化算法

B. Niu, Yan Fan, Pei Zhao, Bing Xue, Li Li, Yujuan Chai
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引用次数: 18

摘要

细菌觅食优化算法(Bacterial foraging optimization, BFO)是一种基于大肠杆菌社会互动隐喻的较新的生物启发式算法。虽然该算法已成功地应用于多种实际的单词优化问题,但在复杂问题的实验中,基本BFO算法的性能较差。为此,本文提出了一种新的细菌觅食优化算法——线性递减趋化步算法(BFO-LDC)。通过对四个经典测试函数的应用以及与基本BFO的比较,充分证明了所提BFO- ldc的性能。实验结果表明,该算法大大提高了基本BFO算法的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Bacterial Foraging Optimizer with Linear Decreasing Chemotaxis Step
Bacterial foraging optimization (BFO) is a relatively new bio-heuristic algorithm which is based on a metaphor of social interaction of E. coli bacteria. Although the algorithm has successfully been applied to many kinds of real word optimization problems, experimentation with complex problems reports that the basic BFO algorithm possesses a poor performance. Thus a novel bacterial foraging optimizer with linear decreasing chemotaxis step (BFO-LDC) algorithm is proposed in the present paper. The performance of the proposed BFO-LDC is amply demonstrated by applying it for four classical test functions and comparing it with basic BFO. And the results obtained show this proposed algorithm greatly improves the efficiency of basic BFO algorithm.
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