Proceedings of the 2014 International Conference on Mechatronics, Control and Electronic Engineering

An improved algorithm for flexible job shop scheduling

Authors
Jindong Han, Yinghong Zhang
Corresponding Author
Jindong Han
Available Online March 2014.
DOI
https://doi.org/10.2991/mce-14.2014.92How to use a DOI?
Keywords
Improved Genetic Algorithm; Crossover probability; mutation probability; Flexible Job Shop Scheduling; Optimization
Abstract
In the traditional genetic algorithm, there are some defects such as precocious, poor stability, slow search speed etc.Summarize previous genetic algorithm, I proposed a Improved Genetic Algorithms , it combination of encoding, crossover probability, mutation probability, etc. and applied to flexible job shop scheduling.This optimization can accelerate convergence and improve search speed, and can effectively improve the stability of operations, effectively overcome premature, to find the optimal solution faster.The experimental results show this improvement more quickly than ever before to find the optimal solution of the genetic algorithm.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
2014 International Conference on Mechatronics, Control and Electronic Engineering (MCE-14)
Part of series
Advances in Intelligent Systems Research
Publication Date
March 2014
ISBN
978-94-62520-31-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/mce-14.2014.92How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jindong Han
AU  - Yinghong Zhang
PY  - 2014/03
DA  - 2014/03
TI  - An improved algorithm for flexible job shop scheduling
BT  - 2014 International Conference on Mechatronics, Control and Electronic Engineering (MCE-14)
PB  - Atlantis Press
SP  - 413
EP  - 417
SN  - 1951-6851
UR  - https://doi.org/10.2991/mce-14.2014.92
DO  - https://doi.org/10.2991/mce-14.2014.92
ID  - Han2014/03
ER  -