An improved algorithm for flexible job shop scheduling
Jindong Han, Yinghong Zhang
Available Online March 2014.
- https://doi.org/10.2991/mce-14.2014.92How to use a DOI?
- Improved Genetic Algorithm; Crossover probability; mutation probability; Flexible Job Shop Scheduling; Optimization
- 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.
- 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 -