Dynamic Scheduling Optimization of Job Shop Based on OCTPN and Hybrid Genetic Algorithms

DOI

10.2991/emeit.2012.269How to use a DOI?

Keywords

Petri net, Hybrid genetic algorithm, Dynamic scheduling, Bi-objective

Abstract

Combining colored Petri net with object-oriented technology, a new object-oriented colored timed Petri net (OCTPN) method was proposed and the scheduling model of a dual-resource constrained job shop was built. The model has good reusability comparing with the model built by process-oriented technology. A hybrid genetic algorithm based on Pareto was proposed and applied to flexible job shop scheduling problem (FJSP) with bi-objective, where the make-span and the production cost were concerned. The algorithm uses the niche technology and many kinds of crossover operations to get the optimum solutions, most importantly, it can generate new scheduling plan rapidly after the disturbance occurred. The simulation experiment is carried out to illustrate that the proposed method can solve bi-objective job shop scheduling problem effectively.

Copyright

© 2012, 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  - Xiaoxia Liu
AU  - Bingyi Yan
AU  - Daizhong Bai
PY  - 2012/09
DA  - 2012/09
TI  - Dynamic Scheduling Optimization of Job Shop Based on OCTPN and Hybrid Genetic Algorithms
BT  - Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
PB  - Atlantis Press
SP  - 1221
EP  - 1224
SN  - 1951-6851
UR  - https://doi.org/10.2991/emeit.2012.269
DO  - 10.2991/emeit.2012.269
ID  - Liu2012/09
ER  -