AFSA-PSO hybrid algorithm based on chaos-collaborative evolution and its application

doi:10.3778/j.issn.1002-8331.2010.32.013

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (32): 48-51.DOI: 10.3778/j.issn.1002-8331.2010.32.013

• 研究、探讨 • Previous Articles Next Articles

AFSA-PSO hybrid algorithm based on chaos-collaborative evolution and its application

ZHANG Chuang-ye¹，MO Yuan-bin¹，HE Deng-xu¹，WANG Wan-min²

1.College of Mathematics and Computer Science，Guangxi University for Nationalities，Nanning 530006，China
2.School of Mechatronics Engineering，Nanchang University，Nanchang 330031，China

Received:2009-04-14 Revised:2009-06-05 Online:2010-11-11 Published:2010-11-11
Contact: ZHANG Chuang-ye

混沌协同人工鱼粒子群混合算法及其应用

张创业¹，莫愿斌¹，何登旭¹，王万民²

1.广西民族大学数学与计算机科学学院，南宁 530006
2.南昌大学机电工程学院，南昌 330031

通讯作者: 张创业

Abstract

Abstract: Aiming at the drawbacks of Artificial Fish-Swarm Algorithm（AFSA），such as being poor in performance of precision and being low in rate of convergence，Chaos Cooperative Artificial Fish-Swarm Algorithm Particle Swarm Optimization（CCAFSA） is presented.By combining AFSA，PSO global parallel search with Simulation Annealing algorithm（SA） search mechanism，and taking the snap leaping function of Simulated Annealing algorithm and the ergodicity of chaos，CCAFSAPSO overcomes the deficiencies of AFSA and PSO in convergence speed，accuracy and the easy trapping into local optimum.The results of the typical function tests further show that CCAFSAPSO algorithm has faster convergence，higher accuracy than similar algorithms.At last the algorithm is applied to process chemical engineering data and gets satisfying results.

Key words: optimization algorithm, Artificial Fish-Swarm Algorithm（AFSA）, Particle Swarm Optimization（PSO）, Simulated Annealing（SA）, chaos, collaborative

摘要： 针对基本人工鱼群算法（AFSA）收敛速度较慢、精度较低和粒子群易陷于局部的缺点，提出了混沌协同人工鱼粒子群混合算法（CCAFSAPSO）。该算法采取AFSA、PSO的全局并行搜索与模拟退火算法（SA）的局部串行搜索机制相结合的搜索方式，并用混沌映射的遍历性和模拟退火算法的突跳功能，克服了AFSA、PSO的收敛速度、求解精度和易陷于局部最优的不足。典型函数测试进一步表明CCAFSAPSO算法和同类算法相比，收敛速度更快、求解精度较高。最后将算法应用于化工数据处理，获得满意效果。

关键词: 优化算法, 人工鱼算法, 粒子群算法, 模拟退火, 混沌, 协同

CLC Number:

TP301.16

ZHANG Chuang-ye¹，MO Yuan-bin¹，HE Deng-xu¹，WANG Wan-min². AFSA-PSO hybrid algorithm based on chaos-collaborative evolution and its application[J]. Computer Engineering and Applications, 2010, 46(32): 48-51.

张创业¹，莫愿斌¹，何登旭¹，王万民². 混沌协同人工鱼粒子群混合算法及其应用[J]. 计算机工程与应用, 2010, 46(32): 48-51.

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AFSA-PSO hybrid algorithm based on chaos-collaborative evolution and its application

混沌协同人工鱼粒子群混合算法及其应用

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