Design of a genetic algorithm for bi-objective flow shop scheduling problems with re-entrant jobs

被引：0
|
作者：
Carman K. M. Lee
Danping Lin
William Ho
Zhang Wu
机构：
[1] Nanyang Technological University,Division of Systems and Engineering Management, School of Mechanical and Aerospace Engineering
[2] Aston University,Operations and Information Management Group, Aston Business School
来源：
The International Journal of Advanced Manufacturing Technology | 2011年 / 56卷
关键词：
Bi-objective; Re-entrant; Genetic algorithm; Flow shop;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper presents a simulated genetic algorithm (GA) model of scheduling the flow shop problem with re-entrant jobs. The objective of this research is to minimize the weighted tardiness and makespan. The proposed model considers that the jobs with non-identical due dates are processed on the machines in the same order. Furthermore, the re-entrant jobs are stochastic as only some jobs are required to reenter to the flow shop. The tardiness weight is adjusted once the jobs reenter to the shop. The performance of the proposed GA model is verified by a number of numerical experiments where the data come from the case company. The results show the proposed method has a higher order satisfaction rate than the current industrial practices.
引用
收藏
页码：1105 / 1113
页数：8
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