基于QPSO的重载齿轮多目标优化设计  

Multi-objective Optimization Design of the Heavy-duty Gear Drive Based on QPSO

作　　者：李盘荣[1] 

机构地区：[1]无锡市广播电视大学,江苏无锡214011

出　　处：《现代机械》2009年第5期43-46,共4页Modern Machinery

摘　　要：粒子群优化算法(PSO)是一种基于群智能的优化方法,量子粒子群优化算法(QPSO)是基于PSO进行改进的算法,规则简单、收敛速度快、易于编程实现。对于多目标、多约束条件的重载齿轮的优化设计,本文提出了一种基于QPSO优化求解的设计方法;实践表明能够快速、有效求得优化解,是求解重载齿轮优化设计问题的一个较好方案。PSO（Particle Swarm Optimization） is a optimization algorithm for swarm intelligence optimization. QPSO （Quantum Particle Swarm Optimization ） is a evolutionary algorithm based on PSO. Compared with other evolutionary algorithm, its converges is more quickly and its roles are simpler ,also the programming is easier. In this paper , QPSO is developed to optimize the multi-objective optimization design of the heavy-duty gear. The results of experiments show that the optimal solution can be quickly and effectively reached with QPSO. Thus QPSO is proved to be an effective method for multi-objective Optimization design of the Heavy-duty Gear.

关 键 词：粒子群优化算法 量子粒子群优化算法 多目标 优化设计 重载齿轮 

分 类 号：TP15[自动化与计算机技术—控制理论与控制工程]