Solving flexible job shop scheduling problem by a multi-swarm collaborative genetic algorithm-Reference-Cited by-同舟云学术

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Solving flexible job shop scheduling problem by a multi-swarm collaborative genetic algorithm

Published:2021-04 Issue:2 Volume:32 Page:261-271
ISSN:1004-4132
Container-title:Journal of Systems Engineering and Electronics
language:
Short-container-title:J. of Syst. Eng. Electron.

Author:

Cuiyu Wang,Yang Li,Xinyu Li

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/5971804/9430100/09430104.pdf?arnumber=9430104

Cited by 18 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A DQL-NSGA-III algorithm for solving the flexible job shop dynamic scheduling problem;Expert Systems with Applications;2024-03

2. A Study of Deep Learning Neural Network Algorithms and Genetic Algorithms for FJSP;Journal of Applied Mathematics;2023-10-25

3. An improved discrete particle swarm optimization for multi-objective flexible job shop scheduling problem under dynamic perturbation;International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023);2023-08-10

4. An Improved Seagull Optimization Algorithm for Flexible Job-shop Scheduling Problem;2023 IEEE 13th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER);2023-07-11

5. Quantum-inspired African vultures optimization algorithm with elite mutation strategy for production scheduling problems;Journal of Computational Design and Engineering;2023-07-04

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