A parallel deep adaptive large neighbourhood search algorithm for distributed heterogeneous hybrid flow shops with mixed-model assembly scheduling-Reference-Cited by-同舟云学术

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A parallel deep adaptive large neighbourhood search algorithm for distributed heterogeneous hybrid flow shops with mixed-model assembly scheduling

Published:2024-04-26 Issue: Volume: Page:1-28
ISSN:0305-215X
Container-title:Engineering Optimization
language:en
Short-container-title:Engineering Optimization

Author:

Shao Weishi¹²³⁴,Shao Zhongshi⁵,Pi Dechang²

Affiliation:

1. School of Computer and Electronic Information/School of Artificial Intelligence, Nanjing Normal University, Nanjing, People's Republic of China

2. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China

3. Information Security and Privacy Protection Technology, Nanjing, People's Republic of China

4. Key Laboratory of Numerical Simulation for Large Scale Complex Systems, Ministry of Education, People's Republic of China

5. School of Computer Science, Shaanxi Normal University, Xi'an, People's Republic of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/0305215X.2024.2328188

Reference53 articles.

1. A survey of multi-factory scheduling

2. Production planning of mixed-model assembly lines: overview and extensions

3. Sequencing mixed-model assembly lines: Survey, classification and model critique

4. A novel shuffled frog-leaping algorithm with reinforcement learning for distributed assembly hybrid flow shop scheduling

5. Carbon-efficient scheduling of flow shops by multi-objective optimization

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