Flexible job shop scheduling model with parallel processes based on genetic algorithm

DOI

10.2991/msmee-17.2017.184How to use a DOI?

Keywords

scheduling model, parallel processes, genetic algorithm.

Abstract

This paper studies the flexible job shop scheduling problem under the condition that with parallel processes. In this paper, we analyses the characteristics of the process parallelism in the job shop scheduling problem, puts forward the concept of parallel efficiency, establishes the flexible job shop scheduling model with parallel processes based on the objective criteria of minimizing the makespan, and designs the model solution algorithm based on genetic algorithm. The feasibility of the scheduling model and the effectiveness of the algorithm are verified by simulation experiments. The parameters of process parallel rate are compared and analyzed. The experimental results show that it is effective to improve the scheduling efficiency by improving the parallelism of the process route.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Bo Bao
AU  - Lin Zhang
AU  - Bo Zhang
PY  - 2017/05
DA  - 2017/05
TI  - Flexible job shop scheduling model with parallel processes based on genetic algorithm
BT  - Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)
PB  - Atlantis Press
SP  - 953
EP  - 958
SN  - 2352-5401
UR  - https://doi.org/10.2991/msmee-17.2017.184
DO  - 10.2991/msmee-17.2017.184
ID  - Bao2017/05
ER  -