Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials

An Effective Local Search for Hybrid Flow Shop Scheduling Problems

Authors
Zhixiong Su, Junmin Yi
Corresponding Author
Zhixiong Su
Available Online January 2016.
DOI
https://doi.org/10.2991/icsmim-15.2016.92How to use a DOI?
Keywords
production scheduling; hybrid flow shop; local search; active schedule
Abstract

To solve the hybrid flow shop scheduling problems with minimum makespan objective, a local search based on the active scheduling technique was proposed. First, a good initial solution was generated by the NEH-based heuristic. Next, a problem-specific local search was developed to improve the initial solution. Last, the experimental results of benchmark instances indicate the effectiveness of the proposed algorithm, which can find the optima for more instances with a small overall average deviation of 3.445% (decreased by 2.359% compared with NEH-based heuristic).

Copyright
© 2016, 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/).

Download article (PDF)

Volume Title
Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials
Series
Advances in Computer Science Research
Publication Date
January 2016
ISBN
978-94-6252-157-5
ISSN
2352-538X
DOI
https://doi.org/10.2991/icsmim-15.2016.92How to use a DOI?
Copyright
© 2016, 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  - Zhixiong Su
AU  - Junmin Yi
PY  - 2016/01
DA  - 2016/01
TI  - An Effective Local Search for Hybrid Flow Shop Scheduling Problems
BT  - Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials
PB  - Atlantis Press
SP  - 496
EP  - 500
SN  - 2352-538X
UR  - https://doi.org/10.2991/icsmim-15.2016.92
DO  - https://doi.org/10.2991/icsmim-15.2016.92
ID  - Su2016/01
ER  -