Dynamic flexible job shop scheduling method based on improved gene expression programming

被引：22

作者：

Zhang, Chunjiang ^{[1
]}

Zhou, Yin ^{[1
]}

Peng, Kunkun ^{[2
]}

Li, Xinyu ^{[1
]}

Lian, Kunlei ^{[3
]}

Zhang, Suyan ^{[4
]}

机构：

[1] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Luoyu Rd 1037, Wuhan 430074, Peoples R China

[2] Wuhan Univ Sci & Technol, Sch Management, Wuhan, Peoples R China

[3] Walmart Technol, Bentonville, AR USA

[4] Capital Aerosp Machinery Co Ltd, Beijing, Peoples R China

来源：

MEASUREMENT & CONTROL | 2021年 / 54卷 / 7-8期

基金：

中国国家自然科学基金; 国家重点研发计划;

关键词：

Dynamic scheduling; flexible job shop scheduling; gene expression programming; variable neighborhood search; ALGORITHMS; SEARCH;

D O I：

10.1177/0020294020946352

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Dynamic scheduling is one of the most important key technologies in production and flexible job shop is widespread. Therefore, this paper considers a dynamic flexible job shop scheduling problem considering setup time and random job arrival. To solve this problem, a dynamic scheduling framework based on the improved gene expression programming algorithm is proposed to construct scheduling rules. In this framework, the variable neighborhood search using four efficient neighborhood structures is combined with gene expression programming algorithm. And, an adaptive method adjusting recombination rate and transposition rate in the evolutionary progress is proposed. The test results on 24 groups of instances with different scales show that the improved gene expression programming performs better than the standard gene expression programming, genetic programming, and scheduling rules.

引用

页码：1136 / 1146

页数：11

共 31 条

[1] Solving comprehensive dynamic job shop scheduling problem by using a GRASP-based approach [J].

Baykasoglu, Adil ;

Karaslan, Fatma S. .

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2017, 55 (11) :3308-3325

[2]

Ben Ali K, 2018, IEEE INT C EMERG, P1137, DOI 10.1109/ETFA.2018.8502560

[3] NSGA-II applied to dynamic flexible job shop scheduling problems with machine breakdown [J].

Chen, Chao ;

Ji, Zhicheng ;

Wang, Yan .

MODERN PHYSICS LETTERS B, 2018, 32 (34-36)

[4] Multi-agent scheduling in a no-wait flow shop system to maximize the weighted number of just-in-time jobs [J].

Chen, Ren-Xia ;

Li, Shi-Sheng ;

Li, Wen-Jie .

ENGINEERING OPTIMIZATION, 2019, 51 (02) :217-230

[5] Evolving priority rules for resource constrained project scheduling problem with genetic programming [J].

Dumic, Mateja ;

Sisejkovic, Dominik ;

Coric, Rebeka ;

Jakobovic, Domagoj .

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 86 :211-221

[6] Comparison of ensemble learning methods for creating ensembles of dispatching rules for the unrelated machines environment [J].

Durasevic, Marko ;

Jakobovic, Domagoj .

GENETIC PROGRAMMING AND EVOLVABLE MACHINES, 2018, 19 (1-2) :53-92

[7]

Ferreira C, 2002, SOFT COMPUTING AND INDUSTRY, P635

[8]

Ferreira C., 2001, Complex Systems, V13, P87

[9] Flexible Job-Shop Rescheduling for New Job Insertion by Using Discrete Jaya Algorithm [J].

Gao, Kaizhou ;

Yang, Fajun ;

Zhou, MengChu ;

Pan, Quanke ;

Suganthan, Ponnuthurai Nagaratnam .

IEEE TRANSACTIONS ON CYBERNETICS, 2019, 49 (05) :1944-1955

[10]

Guo Yong, 2018, Computer Engineering and Applications, V54, P131, DOI 10.3778/j.issn.1002-8331.1708-0183

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