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Application of Neural Networks to Scheduling Problem including Transportation Time

by Qazi Shoeb Ahmad, M. H. Khan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 5
Year of Publication: 2012
Authors: Qazi Shoeb Ahmad, M. H. Khan
10.5120/8560-2152

Qazi Shoeb Ahmad, M. H. Khan . Application of Neural Networks to Scheduling Problem including Transportation Time. International Journal of Computer Applications. 54, 5 ( September 2012), 8-10. DOI=10.5120/8560-2152

@article{ 10.5120/8560-2152,
author = { Qazi Shoeb Ahmad, M. H. Khan },
title = { Application of Neural Networks to Scheduling Problem including Transportation Time },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 5 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 8-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number5/8560-2152/ },
doi = { 10.5120/8560-2152 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:54:54.125495+05:30
%A Qazi Shoeb Ahmad
%A M. H. Khan
%T Application of Neural Networks to Scheduling Problem including Transportation Time
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 5
%P 8-10
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents an approach for finding an optimal schedule of n-jobs and m-machines flowshop scheduling problem involving transportation time between jobs by using neural networks. An algorithm has been given for finding the optimal sequence in scheduling problem without transportation time [2]. Here, this algorithm is applied when transportation times are involved between machines to find the optimal sequence.

References
  1. Agarwal A. , Colak S. and Eryarsoy E. , "Improvement heuristic for the flow-shop scheduling problem: An adaptive-learning approach", European Journal of Operational Research, 169 (3), 801-815 (2006)
  2. Aslan Demir, 'Model development and application based on object oriented neural network for scheduling problem", DEU Research Fund. Project Nr. 0908. 97. 07. 01 (1999)
  3. Baker K. R. , Introduction to sequencing and scheduling, New York, John Wiley
  4. Campell H. , Dudek R. and Smith M. , "A heuristic algorithm for the n-job, m-machine sequencing problem", Management Science, 16, 630-637 (1970)
  5. Fonseca D. J. and Navaresse D. , "Artificial neural networks for job shop simulation", Advanced Engineering Informatics, 16 (4), 241-246 (2002)
  6. Gary R. Weckman, Chandrasekhar V. Ganduri and David A. Koonce, "A neural network job-shop scheduler", Journal of Intelligent Manufacturing, 19:191-201 (2008)
  7. Ho J. C. and Chang Y. L. , "A new heuristic for the n-job, m-machine flow-shop problem", European Journal of Operational Research, 52, 194-202 (1991)
  8. Johnson S. M. , "Optimal two and three-stage production schedules with set-up times included", Naval Research Logistics Quaterly, 1, 61-68 (1954)
  9. Koulamas, Christos, "A new constructive heuristic for the flowshop scheduling problem", European Journal of Operational Research, 105, 66-71 (1988)
  10. McCahon C. S. and Lee E. S. , "Fuzzy Job sequencing for a flowshop", European Journal of Operational Research, 62, 294-301 (1992)
  11. Nawaz M. , Enscore E. and Ham I. , "A heuristic algorithm for the n-job, m-machine flowshop sequencing problem, Omega, 11, 91-95 (1983)
  12. Sabuncuoglu, Ihsan and Gurgun, Burckaan, "A neural network model for scheduling problems", European Journal of Operational Research, 93, 288-299 (1996)
  13. Taillard E. , "Some efficient heuristic methods for the flowshop sequencing problem", European Journal of Operational Research, 47, 65-74 (1990)
  14. Yu H. and Liang W. , "Neural network and genetic algorithmbased hybrid approach to expanded job-shop scheduling", Computers and Industrial Engineering, 39 (3-4), 337-356 (2001)
Index Terms

Computer Science
Information Sciences

Keywords

Neural networks flowshop scheduling transportation time

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