IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v151y2003i3p481-502.html
   My bibliography  Save this article

Augmented neural networks for task scheduling

Author

Listed:
  • Agarwal, Anurag
  • Pirkul, Hasan
  • Jacob, Varghese S.

Abstract

No abstract is available for this item.

Suggested Citation

  • Agarwal, Anurag & Pirkul, Hasan & Jacob, Varghese S., 2003. "Augmented neural networks for task scheduling," European Journal of Operational Research, Elsevier, vol. 151(3), pages 481-502, December.
    • Handle: RePEc:eee:ejores:v:151:y:2003:i:3:p:481-502
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(02)00605-7
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Steinhofel, K. & Albrecht, A. & Wong, C. K., 1999. "Two simulated annealing-based heuristics for the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 118(3), pages 524-548, November.
    2. Sakawa, Masatoshi & Kubota, Ryo, 2000. "Fuzzy programming for multiobjective job shop scheduling with fuzzy processing time and fuzzy duedate through genetic algorithms," European Journal of Operational Research, Elsevier, vol. 120(2), pages 393-407, January.
    3. Biskup, Dirk, 1999. "Single-machine scheduling with learning considerations," European Journal of Operational Research, Elsevier, vol. 115(1), pages 173-178, May.
    4. Satake, Tsuyoshi & Morikawa, Katsumi & Nakamura, Nobuto, 1994. "Neural network approach for minimizing the makespan of the general job-shop," International Journal of Production Economics, Elsevier, vol. 33(1-3), pages 67-74, January.
    5. Sabuncuoglu, Ihsan & Gurgun, Burckaan, 1996. "A neural network model for scheduling problems," European Journal of Operational Research, Elsevier, vol. 93(2), pages 288-299, September.
    6. Pezzella, Ferdinando & Merelli, Emanuela, 2000. "A tabu search method guided by shifting bottleneck for the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 120(2), pages 297-310, January.
    7. Rajendran, Chandrasekharan & Holthaus, Oliver, 1999. "A comparative study of dispatching rules in dynamic flowshops and jobshops," European Journal of Operational Research, Elsevier, vol. 116(1), pages 156-170, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Anurag Agarwal, 2009. "Theoretical insights into the augmented-neural-network approach for combinatorial optimization," Annals of Operations Research, Springer, vol. 168(1), pages 101-117, April.
    2. Selcuk Colak & Anurag Agarwal, 2005. "Non‐greedy heuristics and augmented neural networks for the open‐shop scheduling problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(7), pages 631-644, October.
    3. Anurag Agarwal & Varghese S. Jacob & Hasan Pirkul, 2006. "An Improved Augmented Neural-Network Approach for Scheduling Problems," INFORMS Journal on Computing, INFORMS, vol. 18(1), pages 119-128, February.
    4. Agarwal, Anurag & Colak, Selcuk & Jacob, Varghese S. & Pirkul, Hasan, 2006. "Heuristics and augmented neural networks for task scheduling with non-identical machines," European Journal of Operational Research, Elsevier, vol. 175(1), pages 296-317, November.
    5. Anurag Agarwal & Selcuk Colak & Jason Deane, 2010. "NeuroGenetic approach for combinatorial optimization: an exploratory analysis," Annals of Operations Research, Springer, vol. 174(1), pages 185-199, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Anurag Agarwal & Varghese S. Jacob & Hasan Pirkul, 2006. "An Improved Augmented Neural-Network Approach for Scheduling Problems," INFORMS Journal on Computing, INFORMS, vol. 18(1), pages 119-128, February.
    2. Raaymakers, W. H. M. & Weijters, A. J. M. M., 2003. "Makespan estimation in batch process industries: A comparison between regression analysis and neural networks," European Journal of Operational Research, Elsevier, vol. 145(1), pages 14-30, February.
    3. Jain, A. S. & Meeran, S., 1999. "Deterministic job-shop scheduling: Past, present and future," European Journal of Operational Research, Elsevier, vol. 113(2), pages 390-434, March.
    4. Agarwal, Anurag & Colak, Selcuk & Jacob, Varghese S. & Pirkul, Hasan, 2006. "Heuristics and augmented neural networks for task scheduling with non-identical machines," European Journal of Operational Research, Elsevier, vol. 175(1), pages 296-317, November.
    5. Xingong Zhang & Guangle Yan & Wanzhen Huang & Guochun Tang, 2011. "Single-machine scheduling problems with time and position dependent processing times," Annals of Operations Research, Springer, vol. 186(1), pages 345-356, June.
    6. Ye, Hong & Lin, Zhiping, 2006. "Speed-up simulated annealing by parallel coordinates," European Journal of Operational Research, Elsevier, vol. 173(1), pages 59-71, August.
    7. Zoltán Varga & Pál Simon, 2014. "Examination Of Scheduling Methods For Production Systems," Advanced Logistic systems, University of Miskolc, Department of Material Handling and Logistics, vol. 8(1), pages 111-120, December.
    8. Derya Deliktaş, 2022. "Self-adaptive memetic algorithms for multi-objective single machine learning-effect scheduling problems with release times," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 748-784, September.
    9. Bai, Danyu & Tang, Mengqian & Zhang, Zhi-Hai & Santibanez-Gonzalez, Ernesto DR, 2018. "Flow shop learning effect scheduling problem with release dates," Omega, Elsevier, vol. 78(C), pages 21-38.
    10. Battaïa, Olga & Dolgui, Alexandre, 2013. "A taxonomy of line balancing problems and their solutionapproaches," International Journal of Production Economics, Elsevier, vol. 142(2), pages 259-277.
    11. Sels, Veronique & Craeymeersch, Kjeld & Vanhoucke, Mario, 2011. "A hybrid single and dual population search procedure for the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 215(3), pages 512-523, December.
    12. Wen-Hung Wu & Yunqiang Yin & T C E Cheng & Win-Chin Lin & Juei-Chao Chen & Shin-Yi Luo & Chin-Chia Wu, 2017. "A combined approach for two-agent scheduling with sum-of-processing-times-based learning effect," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(2), pages 111-120, February.
    13. Min Ji & Chou-Jung Hsu & Dar-Li Yang, 2013. "Single-machine scheduling with deteriorating jobs and aging effects under an optional maintenance activity consideration," Journal of Combinatorial Optimization, Springer, vol. 26(3), pages 437-447, October.
    14. Radosław Rudek, 2012. "Scheduling problems with position dependent job processing times: computational complexity results," Annals of Operations Research, Springer, vol. 196(1), pages 491-516, July.
    15. Biskup, Dirk, 2008. "A state-of-the-art review on scheduling with learning effects," European Journal of Operational Research, Elsevier, vol. 188(2), pages 315-329, July.
    16. Vineet Jain & Tilak Raj, 2018. "An adaptive neuro-fuzzy inference system for makespan estimation of flexible manufacturing system assembly shop: a case study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(6), pages 1302-1314, December.
    17. W-H Kuo & D-L Yang, 2008. "Minimizing the makespan in a single-machine scheduling problem with the cyclic process of an aging effect," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(3), pages 416-420, March.
    18. Öner-Közen, Miray & Minner, Stefan, 2017. "Impact of priority sequencing decisions on on-time probability and expected tardiness of orders in make-to-order production systems with external due-dates," European Journal of Operational Research, Elsevier, vol. 263(2), pages 524-539.
    19. Finke, Gerd & Gara-Ali, Ahmed & Espinouse, Marie-Laure & Jost, Vincent & Moncel, Julien, 2017. "Unified matrix approach to solve production-maintenance problems on a single machine," Omega, Elsevier, vol. 66(PA), pages 140-146.
    20. Xu, Jiuping & Song, Xiaoling & Wu, Yimin & Zeng, Ziqiang, 2015. "GIS-modelling based coal-fired power plant site identification and selection," Applied Energy, Elsevier, vol. 159(C), pages 520-539.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:151:y:2003:i:3:p:481-502. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.