计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (2): 46-46.

• 学术探讨 • 上一篇    下一篇

基于向量求值的QPSO算法在多目标优化中的应用

管芳景,须文波,孙俊,薛桢   

  1. 无锡市江南大学
  • 收稿日期:2006-05-16 修回日期:1900-01-01 出版日期:2007-01-11 发布日期:2007-01-11
  • 通讯作者: 管芳景 guanfj

Application of A Vector Evaluated QPSO Algorithm to Multi-objective Optimization

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  1. 无锡市江南大学
  • Received:2006-05-16 Revised:1900-01-01 Online:2007-01-11 Published:2007-01-11

摘要: 在分析了VEGA和VEPSO解决多目标问题的基础上,研究了基于量子行为的微粒群优化算法(QPSO)解决多目标问题, 并提出一种基于向量求值的QPSO多目标优化算法,即VEQPSO。在VEQPSO算法中改进了粒子的进化公式,通过典型的多目标测试函数所做的实验,验证了该算法解决多目标问题的有效性。

关键词: VEGA, VEPSO, 多目标优化, 具有量子行为的微粒群优化算法

Abstract: Based on VEGA and VEPSO, Quantum-behaved Particle Swarm Optimization (QPSO) is investigated to solve multi-objective optimization problem, a Vector Evaluated Quantum- behaved Particle Swarm Optimization algorithm is presented, namely VEQPSO.VEQPSO improves the particle’s evolution formulations. The experiment results of VEQPSO on a classic multiobjective minimization problem show the efficiency of the algorithm, for solving multi-objective optimization problem.

Key words: VEGA, VEPSO, multi-objective optimization, Quantum-behaved particle swarm optimization algorithm