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Niche Improved Particle Swarm Optimization on Geometric Constraint Solving

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5 Author(s)
Chunhong Cao ; Collge of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China ; Chuan Tang ; Dazhe Zhao ; Bin Zhang
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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.

Published in:

Computer-Aided Design and Computer Graphics (CAD/Graphics), 2011 12th International Conference on

Date of Conference:

15-17 Sept. 2011