Niche Improved Particle Swarm Optimization on Geometric Constraint Solving

摘要：

Geometric constraint problem can be transformed to an optimization problem. We can solve the problem with niche improved particle swarm. Classical particle swarm optimization is likely to be trapped into local minima as well as premature. A niche improved particle swarm optimization (NIPSO) based on niche theory was developed. After the update of the particle velocity and position, the outlier particle was identified in the NIPSO by comparing the niche number of every particle, with which the crossover and selection operators were employed sequent for those particles, whose personal best values were less than that of the outlier particle. The experiment shows that it can improve the geometric constraint solving efficiency and possess better convergence property than the compared algorithms.

作者: Chunhong Cao Chuan Tang Dazhe Zhao Bin Zhang ChunYan Han

作者单位: Collge of Information Science and Engineering,Northeastern University,Shenyang 110819,P. R.China Sta State Key Laboratory of Geohazard Prevention and Geoenvironment Protection,Chengdu University of Tec Key Laboratory of Medical Image Computing of Ministry of Education,Northeastern University, Shenyang Collge of Information Science and Engineering,Northeastern University,Shenyang 110819,P. R.China Collge of Information Science and Engineering,Northeastern University,Shenyang 110819,P.R.China

会议类型: 国际会议

会议名称: 2011国际计算机辅助设计与图形学学术会议(CAD/Graphics 2011)

会议地点: 济南

会议语种:英文

页码: 1-4

在线出版日期: 2011-09-15（万方平台首次上网日期，不代表论文的发表时间）