A Self-Learning Discrete Artificial Bee Colony Algorithm for Energy-Efficient Distributed Heterogeneous L-R Fuzzy Welding Shop Scheduling Problem-Reference-Cited by-同舟云学术

A Self-Learning Discrete Artificial Bee Colony Algorithm for Energy-Efficient Distributed Heterogeneous L-R Fuzzy Welding Shop Scheduling Problem

Published:2024-06 Issue:6 Volume:32 Page:3753-3764
ISSN:1063-6706
Container-title:IEEE Transactions on Fuzzy Systems
language:
Short-container-title:IEEE Trans. Fuzzy Syst.

Author:

Yu Fei¹^ORCID,Yin Lvjiang²^ORCID,Zeng Bing³^ORCID,Lu Chao¹^ORCID,Xiao Zhao⁴^ORCID

Affiliation:

1. School of Computer Science, China University of Geosciences, Wuhan, China

2. School of Economics and Management, Hubei University of Automotive Technology, Shiyan, China

3. State key laboratory of offshore wind power equipment and efficient utilization of wind energy, Harbin Electric Corporation Wind Power, Xiangtan, China

4. School of Mechanical Engineering, Hunan University of Science and Technology, Xiangtan, China

Funder

National Natural Science Foundation of China

Key R&D Program Project in Hubei Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/91/10547166/10480649.pdf?arnumber=10480649

Reference46 articles.

1. An Effective Multiobjective Algorithm for Energy-Efficient Scheduling in a Real-Life Welding Shop

2. A knowledge-guided bi-population evolutionary algorithm for energy-efficient scheduling of distributed flexible job shop problem

3. Energy-Efficient Scheduling of Distributed Flow Shop With Heterogeneous Factories: A Real-World Case From Automobile Industry in China

4. Human–Robot Collaborative Scheduling in Energy-Efficient Welding Shop

5. Models for production planning under uncertainty: A review

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