摘要
针对传统的加权系数法和约束法等不能很好解决产品开发任务调度多目标优化的问题,建立了以产品开发时间和成本为目标的多目标优化模型,采用改进的非支配排序遗传算法得出Pareto最优解集,并利用模糊优选法对该解集进行选优,确定了产品开发任务调度的最优执行方案。对两个经典多目标测试函数的求解及对比分析表明了该算法的优越性,结合实例说明了该方法的实施过程及有效性。
Traditional weighted coefficient method and constraint method could not solve the problems of multi-objective optimization of product development task scheduling very well,a multi-objective optimization model was established with the goals of product development time and expenses.A Pareto optimal solution set was obtained by applying NSGA-Ⅱ.This solution set was selected by using fuzzy optimum seeking method,and the optimal implementation plan of product development task scheduling was determined.Superiority of the algorithm was proved by the solutions and comparative analyses of two classical multi-objective test functions.An example was given to illustrate the implementation processes and the effectiveness of the method.
作者
田启华
明文豪
文小勇
杜义贤
周祥曼
TIAN Qihua;MING Wenhao;WEN Xiaoyong;DU Yixian;ZHOU Xiangman(College of Mechanical and Power Engineering,China Three Gorges University,Yichang,Hubei,443002;Civilian Division,Hubei Jiangshan Heavy Industries Co.,Ltd.,Xiangyang,Hubei,441100)
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2018年第22期2758-2766,共9页
China Mechanical Engineering
基金
国家自然科学基金资助项目(51475265)
关键词
产品开发
任务调度
多目标优化
改进的非支配排序遗传算法
模糊优选法
product development
task scheduling
multi-objective optimization
non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)
fuzzy optimum seeking method
