Multi-objective dynamic scheduling algorithm for flexible job-shop problem based on rule orientation

被引：0

作者：

Zhu W. ^{[1
]}

机构：

[1] School of Management Science and Engineering, Henan Institute of Engineering, Zhengzhou

来源：

Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | 2017年 / 37卷 / 10期

关键词：

Dynamic programming; Flexible job-shop; Multi-objective scheduling; Non-dominated sorting genetic algorithm; Rule oriented;

D O I：

10.12011/1000-6788(2017)10-2690-10

中图分类号：

学科分类号：

摘要：

To reduce the complexity of multi-objective dynamic optimization for flexible job-shop scheduling problem (FJSP), an integrated optimization method with flexible resource constraints was proposed and a multi-objective optimization model was built, where the minimum completion time, lowest production cost, maximum equipment utilization rate and delivery satisfaction, also optimal human resource allocation were all concerned. First of all, to restrain the explosive characteristics of combined optimization model, we adopt the rule oriented resources scheduling idea and adjust the probability of rules to ensure the rules with a high probability to be selected to push the search process toward the target direction. Secondly, we adopt the improved non-dominated sorting genetic algorithm (NSGA-II) to obtain the pareto solution sets with different probability values of the rules and use dynamic programming method for solving optimal allocation scheme. Finally, simulation comparison and numerical examples were carried out to illustrate that the proposed method could solve multi-objective FJSP effectively. © 2017, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.

引用

页码：2690 / 2699

页数：9

共 28 条

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