Information entropy based interaction model and optimization method for swarm intelligence

被引：5
|
作者：
Zhu, Yunlong [1 ]
He, Xiaoxian [1 ,2 ]
Hu, Kunyuan [1 ]
Niu, Ben [1 ]
机构：
[1] Chinese Acad Sci, Shenyang Inst Automat, Shenyang 110016, Peoples R China
[2] Cent S Univ, Coll Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China
来源：
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL | 2009年 / 31卷 / 06期
关键词：
information entropy; interaction model; route-exchange algorithm; swarm intelligence;
D O I：
10.1177/0142331208093940
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Inspired by social insects, swarm intelligence has been hotly investigated in recent years as an innovative artificial intelligence technique for solving problems. In this paper, we mainly focus on the information interaction of individuals in swarm intelligence. By using information entropy H(X) and mutual information I(X;Y) of information theory to evaluate the information quality and interaction efficiency, respectively, the interaction model is proposed. Within this model, individuals' information is evaluated with uniform standards, so that more excellent individuals can be selected to influence other individuals by interaction. We validated this model with the route-exchange algorithm, which is proposed for combinatorial optimization. Seven benchmarks of the Traveling Salesman Problem are tested in the experiments. The results are compared with other heuristic algorithms.
引用
收藏
页码：461 / 474
页数：14
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