Swarm intelligence for permutation optimization: A case study of n-queens problem

被引：90

作者：

Hu, XH ^{[1
]}

Eberhart, RC ^{[1
]}

Shi, YH ^{[1
]}

机构：

[1] Purdue Univ, Dept Biomed Engn, W Lafayette, IN 47907 USA

来源：

PROCEEDINGS OF THE 2003 IEEE SWARM INTELLIGENCE SYMPOSIUM (SIS 03) | 2003年

关键词：

D O I：

10.1109/SIS.2003.1202275

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper introduces a modified Particle Swarm Optimizer which deals with permutation problems. Particles are defined as permutations of a group of unique values. Velocity updates are redefined based on the similarity of two particles. Particles change their permutations with a random rate defined by their velocities. A mutation factor is introduced to prevent the current pBest from becoming stuck at local minima. Preliminary study on the n-queens problem shows that the modified PSO is promising in solving constraint satisfication problems.

引用

页码：243 / 246

页数：4

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