一种基于文化算法和量子计算的改进粒子群算法

2012 Eighth International Conference on Computational Intelligence and Security Pub Date : 2012-11-17 DOI:10.1109/CIS.2012.10

X. Gao, Ying Wu, Xiaolei Wang, Xianlin Huang, K. Zenger, Xiaofeng Wang

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引用次数: 1

摘要

为了提高量子粒子群算法的性能，提出了一种新的文化量子粒子群优化算法(CQPSO)。文化框架嵌入到QPSO中，信念空间中存储的知识可以指导QPSO的进化。采用15个高维多模态函数和一个压力容器最优设计问题对该算法进行了研究。数值模拟结果表明，CQPSO确实优于QPSO。

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A Modified PSO Method Based on Cultural Algorithm and Quantum Computing

A novel Cultural Quantum-behaved Particle Swarm Optimization algorithm (CQPSO) is proposed in this paper to improve the performance of the Quantum-behaved PSO (QPSO). The cultural framework is embedded in our QPSO, and the knowledge stored in the belief space can guide the evolution of the QPSO. A total of 15 high-dimensional and multi-modal functions as well as an optimal pressure vessel design problem are employed to investigate the proposed algorithm. Numerical simulations results demonstrate that the CQPSO can indeed outperform the QPSO.

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2012 Eighth International Conference on Computational Intelligence and Security

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