[1]杜占玮,杨永健,孙永雄,等.基于互信息的混合蚁群算法及其在旅行商问题上的应用[J].东南大学学报(自然科学版),2011,41(3):478-481.[doi:10.3969/j.issn.1001-0505.2011.03.009]
 Du Zhanwei,Yang Yongjian,Sun Yongxiong,et al.Hybrid ant colony algorithm based on mutual information and its application to traveling salesman problem[J].Journal of Southeast University (Natural Science Edition),2011,41(3):478-481.[doi:10.3969/j.issn.1001-0505.2011.03.009]
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基于互信息的混合蚁群算法及其在旅行商问题上的应用()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
41
期数:
2011年第3期
页码:
478-481
栏目:
计算机科学与工程
出版日期:
2011-05-20

文章信息/Info

Title:
Hybrid ant colony algorithm based on mutual information and its application to traveling salesman problem
作者:
杜占玮1杨永健1孙永雄1张池军12
(1吉林大学计算机科学与技术学院, 长春 130012)(2吉林财经大学信息学院, 长春 130117)
Author(s):
Du Zhanwei1Yang Yongjian1Sun Yongxiong1Zhang Chijun12
(1 College of Computer Science and Technology, Jilin University, Changchun 130012, China)
(2 College of Information, Jilin University of Finance and Economics, Changchun 130117, China)
关键词:
混合蚁群算法图像配准互信息联合直方图旅行商问题
Keywords:
hybrid ant colony algorithm image matching mutual information joint histogram traveling salesman problem
分类号:
TP301
DOI:
10.3969/j.issn.1001-0505.2011.03.009
摘要:
为了提高蚁群算法的求解性能,从医学图像配准算法的思想出发,提出了一种基于互信息相似度的混合蚁群算法.为了表示最优路径和待配准路径之间的互信息熵,在蚁群算法的概率算子中增加了一个新的相似度影响因子,从而可以增加原算法的全局搜索能力,同时可以加速算法在解空间的搜索速度.将该算法应用在旅行商问题上,根据旅行商问题的特定环境,对混合蚁群算法的算式进行了一定程度的化简,使得算法在解决此类问题时,相应的时间复杂度降低.通过实验与多种传统算法进行对比,结果表明该改进算法在求解性能和跳出局部最小解方面都有一定程度的提高.
Abstract:
To improve the performance of the ant colony algorithm, from the viewpoint of medical image registration, a hybrid ant colony algorithm is proposed based on mutual information similarity. To express the mutual entropy of the optimal path and the matching paths, a new similarity influence factor is added to the probability operator of the ant colony algorithm, which can improve the global search capability and accelerate the search speed. Besides, the proposed algorithm is applied in the traveling salesman problem, and the formulae are simplified in order to decrease time complexity. Compared with the traditional algorithms through experiments, the results demonstrate that the proposed algorithm can improve to some extent the solution performance and the capacity of jumping out of local minimum.

参考文献/References:

[1] 马政德.基于互信息的图像配准并行算法研究与实现[D].长沙:国防科学技术大学计算机科学与技术学院,2007.
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[3] Viola P A.Alignment by maximization of mutual information[D].Cambridge,MA,USA:Massachusetts Institute of Technology,1995.
[4] Colorni A,Dorigo M,Maniezzo V.Distributed optimization by ant colonies[C]//Proceedings of European Conference on Artificial Life.Paris,1991:134-142.
[5] 段海滨.蚁群算法原理及其应用[M].北京:科学出版社,2005:1-10.
[6] Duan H B,Wang D B,Yu X F.Grid-based ACO algorithm for parameters tuning of NLPID controller and its application in flight simulator[J].International Journal of Computational Methods, 2006,3(2):163-175.
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备注/Memo

备注/Memo:
作者简介:杜占玮 (1988—) ,男,硕士生;杨永健 (联系人),男,博士,教授,博士生导师,yyj@jlu.edu.cn.
基金项目:吉林省科技发展计划重点资助项目(20080319)、吉林大学研究生创新基金资助项目(20111064).
引文格式: 杜占玮,杨永健,孙永雄,等.基于互信息的混合蚁群算法及其在旅行商问题上的应用[J].东南大学学报:自然科学版,2011,41(3):478-481.[doi:10.3969/j.issn.1001-0505.2011.03.009]
更新日期/Last Update: 2011-05-20