A hybrid fluid master–apprentice evolutionary algorithm for large-scale multiplicity flexible job-shop scheduling with sequence-dependent set-up time-Reference-Cited by-同舟云学术

A hybrid fluid master–apprentice evolutionary algorithm for large-scale multiplicity flexible job-shop scheduling with sequence-dependent set-up time

Published:2022-12-05 Issue: Volume: Page:1-22
ISSN:0305-215X
Container-title:Engineering Optimization
language:en
Short-container-title:Engineering Optimization

Author:

Ding Linshan¹,Guan Zailin¹^ORCID,Zhang Zhengmin¹^ORCID,Fang Weikang¹,Chen Zhipeng¹,Yue Lei²

Affiliation:

1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, People’s Republic of China

2. School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, People’s Republic of China

Funder

Youth Program of the National Natural Science Foundation of China

the National Key R&D Program of China

International and Hong Kong, Macao and Taiwan High End Talent Exchange Funding of Guangdong Province

Guangzhou Basic and Applied Basic Research Project

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Applied Mathematics,Industrial and Manufacturing Engineering,Management Science and Operations Research,Control and Optimization,Computer Science Applications

Link

https://www.tandfonline.com/doi/pdf/10.1080/0305215X.2022.2145605

Reference38 articles.

1. Solving a parallel-line capacitated lot-sizing and scheduling problem with sequence-dependent setup time/cost and preventive maintenance by a rolling horizon method

2. From Fluid Relaxations to Practical Algorithms for High-Multiplicity Job-Shop Scheduling: The Holding Cost Objective

3. Multi-product continuous plant scheduling: combination of decomposition, genetic algorithm, and constructive heuristic

4. Scheduling jobshops with some identical or similar jobs

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