A reinforcement learning-driven brain storm optimisation algorithm for multi-objective energy-efficient distributed assembly no-wait flow shop scheduling problem-Reference-Cited by-同舟云学术

A reinforcement learning-driven brain storm optimisation algorithm for multi-objective energy-efficient distributed assembly no-wait flow shop scheduling problem

Published:2022-05-12 Issue:9 Volume:61 Page:2854-2872
ISSN:0020-7543
Container-title:International Journal of Production Research
language:en
Short-container-title:International Journal of Production Research

Author:

Zhao Fuqing¹^ORCID,Hu Xiaotong¹,Wang Ling²,Xu Tianpeng¹,Zhu Ningning¹,Jonrinaldi ³

Affiliation:

1. School of Computer and Communication Technology, Lanzhou University of Technology, Lanzhou, People’s Republic of China

2. Department of Automation, Tsinghua University, Beijing, People’s Republic of China

3. Department of Industrial Engineering, Universitas Andalas, Padang, Indonesia

Funder

National Natural Science Foundation of China

Key Research Programs of Science and Technology Commission Foundation of Gansu Province

Lanzhou Science Bureau project

Project of Zhejiang Natural Science Foundation

Project of Gansu Natural Science Foundation

Key talent project of Gansu Province

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2022.2070786

Reference57 articles.

1. Minimising maximum tardiness in assembly flowshops with setup times

2. Self‐adaptive brainstorming for jobshop scheduling in multicloud environment

3. A collaborative optimization algorithm for energy-efficient multi-objective distributed no-idle flow-shop scheduling

4. A competitive memetic algorithm for the distributed two-stage assembly flow-shop scheduling problem

5. No-wait two-stage flowshop problem with multi-task flexibility of the first machine

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