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基于SFLA-PSO算法的几何约束求解
引用本文:于晓鹏,曹春红.基于SFLA-PSO算法的几何约束求解[J].吉林大学学报(信息科学版),2012,30(2):203-206.
作者姓名:于晓鹏  曹春红
作者单位:1.吉林师范大学 计算机学院,吉林 四平 136000;2.东北大学 信息科学与工程学院,沈阳 110819;3.吉林大学 符号计算与知识工程教育部重点实验室,长春 130012
基金项目:南京大学计算机软件新技术国家重点实验室开放课题基金资助项目(KFKT2011B14)
摘    要:为提高求解几何约束问题的效率和收敛性,将几何约束问题等价为求解非线性方程组问题。并将约束问题转化为一个优化问题,采用基于混洗蛙跳(SFLA:Shuffled Frog Leaping Algorithm)和粒子群优化(PSO:Particle Swarm Optimization)算法求解该问题。SFLA-PSO算法采用将SFLA和PSO二者相结合的方法,利用PSO算法进行族群局部搜索,利用SFLA的多种群的进化方法进行族群的混选,相互取长补短,以达到收敛速度快和全局搜索的目的。实验表明,该方法可以提高几何约束求解的效率和收敛性。

关 键 词:几何约束求解  混洗蛙跳算法  粒子群优化算法  
收稿时间:2012-01-04

Geometric Constraint Solving Based on Shuffled Frog Leaping Algorithm and Particle Swarm Optimization
YU Xiao-peng , CAO Chun-hong.Geometric Constraint Solving Based on Shuffled Frog Leaping Algorithm and Particle Swarm Optimization[J].Journal of Jilin University:Information Sci Ed,2012,30(2):203-206.
Authors:YU Xiao-peng  CAO Chun-hong
Institution:1.College of Computer Science,Jilin Normal University,Siping 136000,China;2.College of Information Science and Engineering,Northeastern University,Shen
yang 110819,China;3.Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education,Jilin University,Changchun 130012,China
Abstract:In order to improve the efficiency and convergence property,geometric constraint solving problem is the current hot issues in the constraint-based design research.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 with SFLA-PSO(Shuffled Frog Leaping Algorithm-Particle Swarm Optimization).SFLA-PSO algorithm uses the combination of the two algorithms.It can search in local communities by PSO and use the population of more evolutionary approach to racial mix by SFLA.It can get mutual complementarities and attain convergence fast and the global search.The experiment shows that it can improve the geometric constraint solving efficiency and possess better convergence property than the compared algorithms.
Keywords:geometric constraint solving  shuffled frog leaping algorithm(SFLA)  particle swarm optimization(PSO)
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