中国机械工程

• • 上一篇    下一篇

[生产计划]基于NSGA-Ⅱ的产品开发任务调度多目标优化

田启华1;明文豪1;文小勇2;杜义贤1;周祥曼1   

  1. 1.三峡大学机械与动力学院,宜昌,443002
    2.湖北江山重工有限责任公司民品事业部,襄阳,441100
  • 出版日期:2018-11-25 发布日期:2018-11-27
  • 基金资助:
    国家自然科学基金资助项目(51475265)

Multi-objective Optimization Method of Product Development Task Scheduling Based on NSGA-Ⅱ

TIAN Qihua1;MING Wenhao1;WEN Xiaoyong2;DU Yixian1;ZHOU Xiangman1   

  1. 1.College of Mechanical and Power Engineering, China Three Gorges University, Yichang, Hubei, 443002
    2.Civilian Division, Hubei Jiangshan Heavy Industries Co., Ltd., Xiangyang, Hubei, 441100
  • Online:2018-11-25 Published:2018-11-27

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。

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

Abstract: 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.

Key words: product development, task scheduling, multi-objective optimization, non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ), fuzzy optimum seeking method

中图分类号: