Effective upper and lower bounds for a two-stage reentrant flexible flow shop scheduling problem

流水车间调度 作业车间调度 上下界 计算机科学 数学优化 调度(生产过程) 可重入 整数规划 算法 数学 数学分析 程序设计语言 地铁列车时刻表 操作系统
作者
Shuang Zheng,Zhengwen He,Zhen Yang,Chengbin Chu,Nengmin Wang
出处
期刊:Computers & Operations Research [Elsevier BV]
卷期号:153: 106183-106183 被引量:3
标识
DOI:10.1016/j.cor.2023.106183
摘要

Flow shop scheduling is important in modern industrial manufacturing to improve production efficiency. This paper studies a realistic two-stage reentrant flexible flow shop scheduling problem (TSRFFS) with broad applications in aircraft scheduling, manufacturing, and the medical industry, etc. Given a flow shop with a single machine in Stage 1, a set of parallel machines in Stage 2, and a set of jobs to be processed, the TSRFFS aims to determine the completion time of jobs in Stage 1 and then that in Stage 2, and finally returns to Stage 1, as well as determine the job-to-machine assignment in Stage 2 such that all jobs are served and the total processing time of jobs (makespan) is minimized. The optimal solution properties are investigated, based on which a mixed integer programming mathematical model and a greedy random constructive heuristic for near optimal solutions are proposed. By solving series of a revised parallel machine scheduling problem (Pm||Cmax), a lower bound method is developed. Extensive numerical experiments on 1560 random instances with up to 1000 jobs and 50 realistic airport simulation instances were conducted to demonstrate the effectiveness of the proposed algorithms. The average gap between the proposed upper bound and the best lower bounds is approximately 1.78%, and the average gap between the proposed lower bound and the best upper bounds is 0.91%, which far outperforms state-of-the-art approaches in terms of solution quality and computational time.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
hongdongxiang完成签到,获得积分10
刚刚
刚刚
呆萌代桃发布了新的文献求助10
1秒前
小马甲应助碧蓝紫山采纳,获得10
1秒前
1秒前
小张发布了新的文献求助10
1秒前
2秒前
2秒前
玉米小胚发布了新的文献求助10
3秒前
3秒前
xiami完成签到,获得积分10
4秒前
5秒前
5秒前
JHzazaza发布了新的文献求助10
5秒前
YYT完成签到,获得积分20
5秒前
5秒前
霸气映之发布了新的文献求助10
5秒前
5秒前
6秒前
Bonnie发布了新的文献求助10
6秒前
perfect完成签到,获得积分10
6秒前
向阳完成签到,获得积分10
6秒前
7秒前
小二郎应助有点儿小库采纳,获得10
7秒前
7秒前
7秒前
7秒前
庄海棠完成签到 ,获得积分10
8秒前
Xenia完成签到,获得积分10
8秒前
Mr.Su发布了新的文献求助10
8秒前
9秒前
徐扬完成签到,获得积分20
9秒前
家伟完成签到,获得积分10
9秒前
大方向真完成签到,获得积分10
9秒前
9秒前
smottom应助典雅的土豆采纳,获得10
10秒前
醉眠完成签到,获得积分10
10秒前
10秒前
10秒前
爱吃粑粑发布了新的文献求助10
11秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
Cognitive Neuroscience: The Biology of the Mind 1000
Technical Brochure TB 814: LPIT applications in HV gas insulated switchgear 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Picture Books with Same-sex Parented Families: Unintentional Censorship 500
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
不知道标题是什么 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3969335
求助须知:如何正确求助?哪些是违规求助? 3514162
关于积分的说明 11172430
捐赠科研通 3249456
什么是DOI,文献DOI怎么找? 1794853
邀请新用户注册赠送积分活动 875437
科研通“疑难数据库(出版商)”最低求助积分说明 804809