非支配排序自适应遗传算法的车削优化  

Single Objective Non-dominated Sorting Adaptive Genetic Algorithms(SONSAGA) for Optimal Cutting Conchtion

作　　者：陈青艳[1] 

机构地区：[1]武汉软件工程职业学院,武汉430205

出　　处：《机械设计与研究》2013年第2期69-73,共5页Machine Design And Research

基　　金：武汉市资助市属高校科研项目(2010140)

摘　　要：针对车削切削参数的优化提出了一种单目标非支配排序自适应遗传算法(SONSAGA),算法保留了NSGA-II的精英保留策略、快速非支配排序优点,克服了NSGA-II中取值边界附近多个无法消除的支配点现象。车削实例计算结果获得优于已发表文献的优选值,证明单目标非支配排序的自适应遗传算法用于车削用量参数的优化是有效的。SONSAGA算法设置参数少,包括相对变化量、种群规模、最大遗传代数,能自动调节最大遗传代数以及自适应地得到满足给定相对变化量的优选值,为车削用量优化提出了新思路。A Single Objective Non-dominated Sorting Adaptive Genetic Algorithms （SONSAGA） is developed for the optimal cutting conchtion. The SONSAGA remains the elitisms and fast non-dominated sorting approach for the Non-dominated Sorting Genetic Algorithm II（ NSGA-II）, and SONSAGA overcomes the merits that NSGA-II itself can＇t eliminate the dominated dots nearby the bounds. The SONSAGA simulations for the model＇s practical example show that the results obtained are better than the results in the literature by the standard genetic algorithms. The SONSAGA simulation results also indicate that SONSAGA is very effective for the nonlinear optimization model. The SONSAGA has few parameters, including relative variables, pop size and maximum generation. The SONSAGA and adjust the maximum generation and acquire the optimal cutting conchtion values adaptively. Hence the SONSAGA provides a novel method of the single objective optimization for cutting conchtion.

关 键 词：单目标非支配排序自适应遗传算法(SONSAGA) 切削用量优化 车削 

分 类 号：TH128[机械工程—机械设计及理论]