[1]朱绍伟 徐夫田 滕兆明.一种改进蚁群算法求解最短路径的应用[J].计算机技术与发展,2011,(07):202-205.
 ZHU Shao-wei,XU Fu-tian,TENG Zhao-ming.Application of Improvement Ants Algorithm in Solving Shortest Path[J].,2011,(07):202-205.
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一种改进蚁群算法求解最短路径的应用()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2011年07期
页码:
202-205
栏目:
应用开发研究
出版日期:
1900-01-01

文章信息/Info

Title:
Application of Improvement Ants Algorithm in Solving Shortest Path
文章编号:
1673-629X(2011)07-0202-04
作者:
朱绍伟 徐夫田 滕兆明
山东师范大学信息科学与工程学院山东省分布式计算机软件新技术重点实验室
Author(s):
ZHU Shao-weiXU Fu-tianTENG Zhao-ming
Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology,College of Information Science and Engineering,Shandong Normal University
关键词:
蚁群算法信息素最短路径局部搜索
Keywords:
ants algorithm pheromone shortest path local search
分类号:
TP391.9
文献标志码:
A
摘要:
蚁群算法是一种新型的启发式模拟进化算法,为求解各种复杂的组合问题提供了一种新的思路。虽然蚂蚁个体没有智能,但群体蚂蚁可以通过信息素(pheromone)进行互相交流进而协调工作。自从Marco Dorigo根据蚂蚁觅食的过程,首次提出了蚁群算法并且应用于求解最短路径问题以来,针对蚁群算法的研究一直都没有停止。通过对信息素更新策略、局部搜索算法、随机选择概率三个方面的改进,提高算法的全局最优搜索能力和收敛性。实验结果表明,改进算法有较好的性能
Abstract:
Ant colony algorithm is a novel heuristic simulated evolutionary algorithm,provides a new idea for solving complex problems of combination.Although there is no intelligent individual ant,but groups of ants can be pheromones(pheromone) for further coordination of the exchange.Since the ants foraging Marco Dorigo under the process of the ant colony algorithm was first proposed and applied to solve the shortest path problem,for the ant colony algorithm has not stopped.Based on the pheromone updating strategy,local search algorithm,the probability of randomly selected three areas to improve,improve the algorithm's global search ability and convergence of optimal.Experimental results show that the improved algorithm has better performance

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备注/Memo

备注/Memo:
国家自然科学基金项目(60970004); 山东省研究生教育创新计划资助项目(SDYY10059)朱绍伟(1985-),男,山东泰安人,硕士研究生,研究方向为算法优化、网络路由算法;徐夫田,研究员,硕士生导师,研究方向为金融与财务信息系统
更新日期/Last Update: 1900-01-01