Multi-objective optimization of product development task scheduling under resource constraints

被引：0
|
作者：
Tian Q. [1 ]
Huang J. [1 ]
Ming W. [2 ]
Du Y. [1 ]
Zhou X. [1 ]
Fu J. [1 ]
机构：
[1] College of Mechanical and Power Engineering, China Three Gorges University, Yichang
[2] Hubei EVE dynamic Co., Ltd., Square Ternary Technology Center, Jingmen
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2022年 / 28卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Fast elitist non-dominated sorting genetic algorithm; Learning and forgetting effects; Multi-objective ideal point method; Multi-objective optimization; Product development; Resource constraint; Task scheduling;
D O I：
10.13196/j.cims.2022.02.020
中图分类号：
学科分类号：
摘要：
In the process of product development task scheduling, there are resource constraints and learning and forgetting effects, which usually require optimization decisions for multiple objectives. By defining the average resource utilization rate, a learning forgetting effect matrix was proposed. By combining with the multi-stage iterative model of coupling design and taking the resource utilization rate of each stage as a constraint, a multi-objective optimization mathematical model of task scheduling time and cost with learning and forgetting effects under resource constraints was established. The Pareto optimal solution set was solved with the improved NSGA-Ⅱgenetic algorithm, and the solution set was optimized by the improved multi-objective ideal point method to obtain the optimal task scheduling scheme. Taking the development process of an electric vehicle as an example, it verified that the optimization model could reduce product development time, reduce product development costs and increase the overall resource utilization rate. © 2022, Editorial Department of CIMS. All right reserved.
引用
收藏
页码：564 / 573
页数：9
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