Improved iterated greedy algorithm for reentrant flow shop scheduling problem

被引：0

作者：

Wu, Xiuli ^{[1
]}

Li, Yuxin ^{[1
]}

Kuang, Yuan ^{[1
]}

Cui, Jianjie ^{[1
]}

机构：

[1] College of Mechanical Engineering, University of Science and Technology Beijing, Beijing,100083, China

来源：

Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2024年 / 30卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Chromosomes - Job shop scheduling - Learning algorithms - Learning systems - Machine shop practice;

D O I：

10.13196/j.cims.2022.1019

中图分类号：

学科分类号：

摘要：

The reentrant hybrid flow shop adds the reentrant feature to the hybrid flow shop and has a higher scheduling complexity.To solve the reentrant hybrid flow shop scheduling problem,a scheduling optimization model was established with the objective of minimizing the maximum completion time,and then a Learning Iterated Greedy algorithm with Elite Adjustment(LIG-EA)was proposed.The LIG-EA algorithm used job-based encoding,and then decoded the reconstituted chromosomes.The population was divided into two parts,elite individuals and ordinary individuals,and elite destruction with reconstruction and chromosome adjustment based on key jobs were carried out for elite individuals,and the construction of learning mechanisms and destruction with reconstruction for ordinary individuals.To improve the initial population quality,the NEH heuristic algorithm was used for population initialization,and the insertion validity judgment was added to the reconstruction operation for the re-entry characteristics of the reentrant hybrid flow shop to improve the speed of the algorithm.Through extensive experiments,the results showed that the LIG-EA algorithm could effectively solve the reentrant hybrid flow shop scheduling problem. © 2024 CIMS. All rights reserved.

引用

页码：2364 / 2380

共 50 条

[41] Optimizing distributed no-wait flow shop scheduling problem with setup times and maintenance operations via iterated greedy algorithm
Miyata, Hugo Hissashi
Nagano, Marcelo Seido
JOURNAL OF MANUFACTURING SYSTEMS, 2021, 61 (61) : 592 - 612
[42] An effective iterated greedy algorithm for blocking hybrid flow shop problem with due date window
Missaoui, Ahmed
Boujelbene, Younes
RAIRO-OPERATIONS RESEARCH, 2021, 55 (03) : 1603 - 1616
[43] Hybrid Bacterial Iterated Greedy Heuristics for the Permutation Flow Shop Problem
Balazs, Krisztian
Horvath, Zoltan
Koczy, Laszlo T.
2012 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2012,
[44] Solving the Reentrant Permutation Flow-Shop Scheduling Problem with a Hybrid Genetic Algorithm
Chen, Jen Shiang
Pan, Jason Chao Hsien
Lin, Chien Min
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE, 2009, 16 (01): : 23 - 31
[45] Intelligent Optimization Under Multiple Factories: Hybrid Flow Shop Scheduling Problem with Blocking Constraints Using an Advanced Iterated Greedy Algorithm
Wang Y.
Wang Y.
Han Y.
Li J.
Gao K.
Nojima Y.
Complex System Modeling and Simulation, 2023, 3 (04): : 282 - 306
[46] Artificial bee colony algorithm including some components of iterated greedy algorithm for permutation flow shop scheduling problems
Oğuzhan Ahmet Arık
Neural Computing and Applications, 2021, 33 : 3469 - 3486
[47] Bi-objective reentrant hybrid flowshop scheduling: an iterated Pareto greedy algorithm
Ying, Kuo-Ching
Lin, Shih-Wei
Wan, Shu-Yen
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2014, 52 (19) : 5735 - 5747
[48] Artificial bee colony algorithm including some components of iterated greedy algorithm for permutation flow shop scheduling problems
Arik, Oguzhan Ahmet
NEURAL COMPUTING & APPLICATIONS, 2021, 33 (08): : 3469 - 3486
[49] An Improved Reentrant-Bottleneck Heuristic for the Reentrant Hybrid Flow Shop Scheduling
Yan XiaoYan
Wu XiuLi
2020 CHINESE AUTOMATION CONGRESS (CAC 2020), 2020, : 4170 - 4175
[50] An Iterated Local Search Algorithm for the Lot-Streaming Flow Shop Scheduling Problem
Sang, Hongyan
Gao, Liang
Li, Xinyu
ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH, 2014, 31 (06)

← 1 2 3 4 5 →