An improved discrete particle swarm optimization algorithm for TSP

被引：9
|
作者：
Zhang, Changsheng [1 ]
Sun, Jigui [1 ]
Wang, Yan [1 ]
Yang, Qingyun [2 ]
机构：
[1] Jilin Univ, Coll Comp Sci & Technol, Changchun, Peoples R China
[2] Chinese Acad Sci, Changchun Inst Opt Fine Mech & Phys, Beijing 100864, Peoples R China
来源：
PROCEEDING OF THE 2007 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE AND INTELLIGENT AGENT TECHNOLOGY, WORKSHOPS | 2007年
关键词：
D O I：
10.1109/WI-IATW.2007.38
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
An Improved discrete particle swarm optimization (DPSO)-based algorithm for the traveling salesman problem (TSP) is proposed In order to overcome the problem of premature convergence, a novel depressor is proposed and a diversity measure to control the swarm is also introduced which can be used to switch between the attractor and depressor. The proposed algorithm has been applied to a set of benchmark problems and compared with the existing algorithms for solving TSP using swarm intelligence. The results show that it can prevent premature convergence to a high degree, but still keeps a rapid convergence like the basic DPSO.
引用
收藏
页码：35 / +
页数：2
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