The distributed permutation flowshop scheduling problem: A genetic algorithm approach

DOI

10.2991/icmii-15.2015.68How to use a DOI?

Keywords

Distributed permutation flowshop scheduling; Genetic algorithms; Design of experiments.

Abstract

We consider solving a distributed permutation flowshop scheduling problem (DPFSP) with the objective of minimizing makespan. The problem has two dimensions: assigning jobs to factories and scheduling the jobs assigned to each factory. We use GA to solve this problem. In the proposed algorithm we employ some standard techniques like one point crossover and swap mutation. Computational experiments show that the proposed GA produces improved results than original ones but not powerful enough to produce better ones than the known best solutions. Based on this study we will redesign the standard GA implementation by using structural information from the problem. Combining GA with constraint programming and other heuristics to design hybrid search algorithms will also be a valuable direction for further study.

Copyright

© 2015, 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  - Yan Li
AU  - Zhigang Chen
PY  - 2015/10
DA  - 2015/10
TI  - The distributed permutation flowshop scheduling problem: A genetic algorithm approach
BT  - Proceedings of the 3rd International Conference on Mechatronics and Industrial Informatics
PB  - Atlantis Press
SP  - 381
EP  - 384
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmii-15.2015.68
DO  - 10.2991/icmii-15.2015.68
ID  - Li2015/10
ER  -