DocumentCode
2254676
Title
An improved particle swarm optimization algorithm for geometric constraint solving problem
Author
Cao, Chun-hong ; Zhang, Chang-sheng ; Wang, Li-Min
Author_Institution
Collge of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Volume
4
fYear
2010
fDate
11-14 July 2010
Firstpage
1335
Lastpage
1838
Abstract
Geometric constraint problem is equivalent to the problem of solving a set of nonlinear equations substantially. The constraint problem can be transformed to an optimization problem. We can solve the problem by an improved PSO algorithm (IPSO), which is based on the “alldifferent” constraint. It combines the particle swarm optimization algorithm with genetic operators together effectively. When a particle is going to stagnate, the mutation operator is used to search its neighborhood. The experiment indicates that the algorithm can be used to solve geometric constraint problem effectively.
Keywords
constraint theory; genetic algorithms; geometry; nonlinear equations; particle swarm optimisation; alldifferent constraint; genetic operator; geometric constraint solving problem; improved PSO algorithm; mutation operator; nonlinear equation; optimization problem; particle swarm optimization; Algorithm design and analysis; Convergence; Equations; Mathematical model; Optimization; Particle swarm optimization; Schedules; Fitness computation; Geometric constraint; Particle swarm optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location
Qingdao
Print_ISBN
978-1-4244-6526-2
Type
conf
DOI
10.1109/ICMLC.2010.5580958
Filename
5580958
Link To Document