增强排列编码遗传算法的自组织迁移技术

IF 0.3 Q4 MANAGEMENT
K. Dinesh, Rajakumar R, R. Subramanian
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引用次数: 1

摘要

遗传算法(GA)是用于解决各种优化问题的众所周知的优化算法。遗传算法基于进化原理,有效地解决了大规模问题。此外,它还结合了各种混合技术,以在复杂问题中获得最佳性能。然而,自组织是一种流行的模式,它从个体之间的局部互动中获得全球秩序。采用自组织和遗传算法相结合的方法来提高算法的收敛性能。本文提出了一种双向自组织迁移技术来改进遗传算法,以实现种群的收敛性和均衡多样性。在旅行商问题的标准试验台上进行了实验,并从TSPLIB中获得了实例。因此,在各种参数度量方面,该算法与现有的经典遗传算法相比显示出了优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Self-organisation migration technique for enhancing the permutation coded genetic algorithm
Genetic algorithm (GA) is well-known optimisation algorithm for solving various kinds of the optimisation problems. GA is based on the evolutionary principles and effectively solves the large-scale problem. In addition, it incorporates the variety of hybrid techniques to achieve the best performance in complex problems. However, self-organisation is one of the popular model, which acquire global order from the local interaction among the individuals. The combined version of self-organisation and genetic algorithm are adopted to improve the performance in attaining the convergence. This paper proposes a bi-directional self-organisation migration technique for improving the genetic algorithm which achieves the convergence and well-balanced diversity in the population. The experimentation is conducted on the standard test-bed of travelling salesman problem and instances are obtained from TSPLIB. Thus, the proposed algorithm has shown its dominance with the existing classical GA in terms of various parameter metrics.
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来源期刊
International Journal of Applied Management Science
International Journal of Applied Management Science Business, Management and Accounting-Strategy and Management
CiteScore
1.20
自引率
0.00%
发文量
21
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