摘要
针对产品族规划中平台参数与定制参数的主从关联特点,建立了产品族双层规划模型。上层模型进行平台参数的决策,下层模型用于变型产品定制参数的求解。上层平台参数赋予值后,下层每个子规划能够在一定条件下不依赖平台参数进行求解。利用多项式响应面法拟合下层子规划最优值函数,把双层数学模型转变成单层模型,在约束范围内利用遗传算法进行优化求解,从而确定平台参数和定制参数取值。以卷筒产品族的设计优化为例,验证了该方法和模型的有效性。
According to the leader-follower characteristics between platform variables and custom variables in product family planning,a bi-level programming model and bi-level optimization model of product family planning are setup; The upper layer is the leader model to decision-making for platform parameters,and the lower layer is the follower model to decision-making for customization parameters in product variants. After the values of platform variables in the upper level model are assigned,each sub planning of the lower layer can be solved without relying on the platform parameters under certain conditions. The polynomial response surface method is used to fit the optimal function of the lower level programming. Then,the genetic algorithm is applied to solve the bi-level optimization model of the product family to determine the value of the platform parameters. Furthermore,the platform parameter values are substituted into the lower sub-plan to obtain the custom parameter values. Finally,an example on optimal design of product family for drum group is used to demonstrate the feasibility of the established model and proposed method.
作者
程贤福
高东山
万丽云
CHENG Xianfu;GAO Dongshan;WAN Liyun(School of Mechatronics ＆ Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China)
出处
《机械设计与研究》
CSCD
北大核心
2018年第3期140-144,共5页
Machine Design And Research
基金
国家自然科学基金资助项目(51765019、71462007)
关键词
产品族优化
产品平台
双层规划
多项式响应面拟合
遗传算法
product family optimization
product platform
bi-level programming
polynomial response surface fitting
genetic algorithm
