蚁群算法的研究现状及其展望

段海滨,王道波,于秀芬

中国工程科学 ›› 2007, Vol. 9 ›› Issue (2) : 98 -102.

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中国工程科学 ›› 2007, Vol. 9 ›› Issue (2) : 98 -102.

蚁群算法的研究现状及其展望

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Ant Colony Algorithm:Survey and Prospect

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摘要

蚁群算法是近几年优化领域中新出现的一种启发式仿生类并行智能进化系统,该算法采用分布式并 行计算和正反馈机制,易于与其他方法结合,目前已经在众多组合优化领域中得到广泛应用。在介绍基本蚁群 算法数学模型的基础上,列举了进入21世纪以来部分具有代表性的蚁群算法改进模型及其应用情况,然后重点 从算法的模型改进、理论分析、并行实现、应用领域、硬件实现、智能融合等角度对蚁群算法在今后的研究方 向作了系统分析与展望。

Abstract

 Ant colony algorithm is a novel category of bionic meta唱heuristic system, and parallel computation and positive feedback mechanism are adopted in this algorithm. Ant colony algorithm, which has strong robustness and is easy to combine with other methods in optimization, has wide application in various combined optimization fields. Based on the introduction of the mathematical model of basic ant colony algorithm, typical improved models and applications of the ant colony algorithm in the21st century are listed. Finally, based on the systematic address of model improvement, theoretical analysis, parallel realization, application field,  hardware realization and intelligent combination, the key issues and prospects of the ant colony algorithm are proposed in detail.

关键词

蚁群算法 / 信息素 / 正反馈 / 优化

Key words

ant colony algorithm / pheromone / positive feedback / optimization

Author summay

段海滨(1976-),男,山东东营市人,博士,北京航空航天大学硕士生导师

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段海滨,王道波,于秀芬 蚁群算法的研究现状及其展望[J]. 中国工程科学, 2007, 9(2): 98-102 DOI:

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