| 蚁群算法的改进及在TSP问题上的仿真验证 |
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| 引用本文： | 陈佑健,陈佐健.蚁群算法的改进及在TSP问题上的仿真验证[J].计算机工程与设计,2006,27(14):2691-2693. |
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| 作者姓名： | 陈佑健 陈佐健 |
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| 作者单位： | 1. 福州电业局,福建,福州,350009
2. 南京市质量技术监督局,江苏,南京,210018 |
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| 摘 要： | 蚁群算法是一种新型的模拟进化算法，具有正反馈、分布式计算等特点。在介绍蚁群算法基本原理的基础上，针对基本蚁群算法求解速度缓慢、容易陷入局部最优等特点，采用分区搜索的思想，提出了一种改进的蚁群算法。它将搜索区域分成几个较小的区域进行局部搜索，得到了局部较优解，以此产生蚁群算法在全局搜索时的初始信息素分布，并结合局部与全局信息素调整等策略，大大地加速了算法的收敛速度。在TSP旅行商问题上的仿真验证表明它是可行性和有效性的。
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| 关 键 词： | 群集智能 蚁群算法 分区搜索 信息素 旅行商问题 |
| 文章编号： | 1000-7024（2006）14-2691-03 |
| 收稿时间： | 2005-05-20 |
| 修稿时间： | 2005-05-20 |
Improvement of ACA and its simulation on TSP |
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| CHEN You-jian,CHEN Zuo-jian.Improvement of ACA and its simulation on TSP[J].Computer Engineering and Design,2006,27(14):2691-2693. |
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| Authors: | CHEN You-jian CHEN Zuo-jian |
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| Affiliation: | 1, Fuzhou Electric Power Industry Bureau, Fuzhou 350009, China; 2. Nanjing Bureau of Quality and Technical Supervision, Nanjing 210018, China |
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| Abstract: | Ant colony algorithm(ACA) is a novel simulated evolutionary algorithm with the characteristic of positive feedback and dis-tributed computation,buthas the shortcoming of stagnation.After the basic theory of ACA is introduced,an improved ACA combined with the idea of subarea's searching to overcome the shortcoming of ACA is proposed.The main idea of improved ACA is followed: first,the searching area is divided into some subareas to search for local suboptimal solutions;and the initial pheromone's distribution for global searching is given;then the local and the global pheromone updating to get optimal solution are combined.The simulation result of TSP demonstrates its feasibility and efficiency. |
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| Keywords: | swarm intelligence ant colony algorithm(ACA) subarea's searching pheromone traveling salesman problem(TSP) |
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