Proceedings of the 2018 International Conference on Mathematics, Modelling, Simulation and Algorithms (MMSA 2018)

Minimizing the Maximum Flow Time for Flexible Job Shop Problem with Parallel Machines Considering Release Time

Authors
Xi Xiang, Changchun Liu, Lixin Miao
Corresponding Author
Xi Xiang
Available Online March 2018.
DOI
10.2991/mmsa-18.2018.47How to use a DOI?
Keywords
flexible job shop problem; parallel machines; flow time
Abstract

This paper studies a flexible job shop problem with parallel machines considering release time. The objective aims to minimize the maximum flow time. A property which can reduce the dimension of solution space is proposed. A branch-and-bound algorithm is proposed to solve the problem. Through numerical experiments, the proposed algorithm is proved to be both effective and efficient in solving this flexible job shop problem.

Copyright
© 2018, 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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Volume Title
Proceedings of the 2018 International Conference on Mathematics, Modelling, Simulation and Algorithms (MMSA 2018)
Series
Advances in Intelligent Systems Research
Publication Date
March 2018
ISBN
978-94-6252-499-6
ISSN
1951-6851
DOI
10.2991/mmsa-18.2018.47How to use a DOI?
Copyright
© 2018, 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/).

Cite this article

TY  - CONF
AU  - Xi Xiang
AU  - Changchun Liu
AU  - Lixin Miao
PY  - 2018/03
DA  - 2018/03
TI  - Minimizing the Maximum Flow Time for Flexible Job Shop Problem with Parallel Machines Considering Release Time
BT  - Proceedings of the 2018 International Conference on Mathematics, Modelling, Simulation and Algorithms (MMSA 2018)
PB  - Atlantis Press
SP  - 208
EP  - 211
SN  - 1951-6851
UR  - https://doi.org/10.2991/mmsa-18.2018.47
DO  - 10.2991/mmsa-18.2018.47
ID  - Xiang2018/03
ER  -