Improved Genetic Algorithm to Solve FJc|M<sub>ij</sub>|C<sub>max</sub> Scheduling Problem-Reference-Cited by-同舟云学术

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Improved Genetic Algorithm to Solve FJc|M_ij|C_max Scheduling Problem

Published:2021-10-22 Issue: Volume: Page:
ISSN:
Container-title:2021 China Automation Congress (CAC)
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Author:

Zhang Jianxin¹,Guo Zhenhua¹

Affiliation:

1. Inner Mongolia University of Technology Inner Mongolia Key Laboratory of Mechanical and Electrical Control,College of Electric Power,Hohhot,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9727224/9727236/09727357.pdf?arnumber=9727357

Reference12 articles.

1. Flexible job shop scheduling based on improved artificial bee colony algorithm[J];wang;Modular Machine Tool & Automatic Manufacturing Technique,2021

2. A whale swarm optimization algorithm for solving flexible job shop scheduling problem[J];luan;Mechanical Science and Technology for Aerospace Engineering,2020

3. A heuristic algorithm for solving flexible job shop scheduling problem[J];mohsen;International Journal of Advanced Manufacturing Technology,2014

4. A variable neighborhood search based genetic algorithm for flexible job shop scheduling problem

5. An improve genetic algorithm for solving flexible job shop scheduling problem[J/OL];wang;Journal of Chongqing University of Technology(Natural Science),2021

Cited by 1 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 new solution encoding scheme for solving the Flexible Job-Shop Scheduling Problem;2023 IEEE Congress on Evolutionary Computation (CEC);2023-07-01

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