Adaptive immune quantum-behaved particle swarm optimization parallel algorithm

doi:10.3778/j.issn.1002-8331.2010.21.009

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (21): 34-36.DOI: 10.3778/j.issn.1002-8331.2010.21.009

• 研究、探讨 • Previous Articles Next Articles

Adaptive immune quantum-behaved particle swarm optimization parallel algorithm

CHENG Xin-wen

School of Computer，Sichuan University of Science & Engineering，Zigong，Sichuan 643000，China

Received:2010-01-25 Revised:2010-05-26 Online:2010-07-21 Published:2010-07-21
Contact: CHENG Xin-wen

自适应免疫量子粒子群优化并行算法

成新文

四川理工学院计算机学院，四川自贡 643000

通讯作者: 成新文

Abstract

Abstract: The Adaptive Immune Quantum-behaved Particle Swarm Optimization Parallel algorithm（AIQPSOP） is presented.In order to escape from premature convergence and lacking good direction in particles the evolutionary process，quantum technology and immunologic mechanism are employed，and an adaptive immune quantum-behaved particle swarm optimization algorithm is provided.Meanwhile，according to larger calculation and longer consumed time，parallel computation technology is introduced into the provided algorithm too.Simulation experiments show that the presented particle algorithm has better performance.

Key words: particle swarm optimization, quantum technology, immunologic mechanism, parallel computation

摘要： 提出了自适应免疫量子粒子群优化并行算法。为了克服粒子群优化算法早熟收敛以及粒子在进化过程中缺乏很好的方向指导的问题，采用了量子技术以及免疫机制，从而获得了一个自适应免疫量子粒子群优化算法。同时，针对该算法计算量大、耗时长的缺点，结合已有的并行计算技术，构造出了该算法的并行计算方法。仿真实验表明所提并行算法具有较好的性能。

关键词: 粒子群优化, 量子技术, 免疫机制, 并行计算

CLC Number:

TP301

CHENG Xin-wen. Adaptive immune quantum-behaved particle swarm optimization parallel algorithm[J]. Computer Engineering and Applications, 2010, 46(21): 34-36.

成新文. 自适应免疫量子粒子群优化并行算法[J]. 计算机工程与应用, 2010, 46(21): 34-36.

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Adaptive immune quantum-behaved particle swarm optimization parallel algorithm

自适应免疫量子粒子群优化并行算法

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