基于元胞多目标遗传算法的蜗杆优化设计  

Worm optimization design based on cellular multi-objective genetic algorithm

作　　者：朱大林[1] 詹腾[1] 

机构地区：[1]三峡大学水电机械设备设计与维护湖北省重点实验室,湖北宜昌443002

出　　处：《计算机工程与应用》2015年第13期263-270,共8页Computer Engineering and Applications

摘　　要：为研究蜗杆传动的多目标优化问题,提出一种自适应差分进化的元胞多目标遗传算法。该算法针对元胞遗传算法的特点,对基本的差分进化策略进行改进,得到一种参数自适应控制策略。将该算法与目前性能优异的4种多目标进化算法在三目标的基准测试函数进行对比实验,结果表明所提算法相对于其他算法具有明显的优势,能够在保证良好收敛性的同时,使获得的Pareto前端分布性更加均匀,覆盖范围更广;工程实例求解结果也表明了算法的工程可行性。In order to solve the multi-objective optimization design model of worm transmission,an Adaptive Differential Evolution Cellular genetic algorithm（ADECell）is proposed.In connection with the characteristics of cellular genetic algorithm,this algorithm improves the basic differential evolution strategy and obtains a parameter adaptive control strategy.The proposed algorithm is compared with 4 state-of-the-art multi-objective evolutionary algorithms on the three-objective benchmark test problems.Simulation results show that ADECell can ensure good convergence while has uniform distribution and wild coverage area for obtained Pareto optimum solution.The results of engineering example show the feasibility of the proposed algorithm.

关 键 词：蜗杆传动 元胞遗传算法 差分进化 多目标优化 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]