IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v141y2013i1p360-365.html
   My bibliography  Save this article

A flexible dispatching rule for minimizing tardiness in job shop scheduling

Author

Listed:
  • Chen, Binchao
  • Matis, Timothy I.

Abstract

In this paper, a dispatching rule called the Weight Biased Modified RRrule is developed that minimizes the mean tardiness of weighted jobs in an m-machine job shop, i.e. Jm|ri,recrc|∑iTik where Tik denotes the tardiness of those jobs with weight greater than a specified threshold level k. It is a significant extension of the RRrule in that it has linear complexity and considers weighted jobs. In addition, the WBMR rule allows for biasing of the schedule towards meeting the deadline of high priority jobs through the tuning of a single parameter, where such an effect is quantified by evaluating tardiness at different truncation thresholds. Numerical testing demonstrates the ability of the WBMR to outperform other traditional rules at various congestion and due-date tightness levels.

Suggested Citation

  • Chen, Binchao & Matis, Timothy I., 2013. "A flexible dispatching rule for minimizing tardiness in job shop scheduling," International Journal of Production Economics, Elsevier, vol. 141(1), pages 360-365.
  • Handle: RePEc:eee:proeco:v:141:y:2013:i:1:p:360-365
    DOI: 10.1016/j.ijpe.2012.08.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527312003672
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2012.08.019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Ari P. J. Vepsalainen & Thomas E. Morton, 1987. "Priority Rules for Job Shops with Weighted Tardiness Costs," Management Science, INFORMS, vol. 33(8), pages 1035-1047, August.
    2. Zhou, Hong & Cheung, Waiman & Leung, Lawrence C., 2009. "Minimizing weighted tardiness of job-shop scheduling using a hybrid genetic algorithm," European Journal of Operational Research, Elsevier, vol. 194(3), pages 637-649, May.
    3. Ramasesh, R, 1990. "Dynamic job shop scheduling: A survey of simulation research," Omega, Elsevier, vol. 18(1), pages 43-57.
    4. Raghu, T. S. & Rajendran, Chandrasekharan, 1993. "An efficient dynamic dispatching rule for scheduling in a job shop," International Journal of Production Economics, Elsevier, vol. 32(3), pages 301-313, November.
    5. N/A, 1984. "Confidence Intervals," National Institute Economic Review, National Institute of Economic and Social Research, vol. 109(1), pages 33-37, August.
    6. George S. Fishman, 1971. "Estimating Sample Size in Computing Simulation Experiments," Management Science, INFORMS, vol. 18(1), pages 21-38, September.
    7. Michael H. Bulkin & John L. Colley & Harry W. Steinhoff, Jr., 1966. "Load Forecasting, Priority Sequencing, and Simulation in a Job Shop Control System," Management Science, INFORMS, vol. 13(2), pages 29-51, October.
    8. Kenneth R. Baker, 1984. "Sequencing Rules and Due-Date Assignments in a Job Shop," Management Science, INFORMS, vol. 30(9), pages 1093-1104, September.
    9. 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. Jiang, Min & Huang, George Q., 2022. "Intralogistics synchronization in robotic forward-reserve warehouses for e-commerce last-mile delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    2. Mallor, Fermin & Guardiola, Ivan G., 2014. "The Weibull scheduling index for client driven manufacturing processes," International Journal of Production Economics, Elsevier, vol. 150(C), pages 225-238.
    3. A. S. Xanthopoulos & D. E. Koulouriotis, 2018. "Cluster analysis and neural network-based metamodeling of priority rules for dynamic sequencing," Journal of Intelligent Manufacturing, Springer, vol. 29(1), pages 69-91, January.
    4. Ferreira, Cristiane & Figueira, Gonçalo & Amorim, Pedro, 2022. "Effective and interpretable dispatching rules for dynamic job shops via guided empirical learning," Omega, Elsevier, vol. 111(C).
    5. Hübl, Alexander & Jodlbauer, Herbert & Altendorfer, Klaus, 2013. "Influence of dispatching rules on average production lead time for multi-stage production systems," International Journal of Production Economics, Elsevier, vol. 144(2), pages 479-484.
    6. Karapetyan, Daniel & Mitrovic Minic, Snezana & Malladi, Krishna T. & Punnen, Abraham P., 2015. "Satellite downlink scheduling problem: A case study," Omega, Elsevier, vol. 53(C), pages 115-123.
    7. Mohamed Habib Zahmani & Baghdad Atmani, 2021. "Multiple dispatching rules allocation in real time using data mining, genetic algorithms, and simulation," Journal of Scheduling, Springer, vol. 24(2), pages 175-196, April.
    8. Tanja Mlinar & Philippe Chevalier, 2016. "Pooling heterogeneous products for manufacturing environments," 4OR, Springer, vol. 14(2), pages 173-200, June.
    9. Xiong, Hegen & Fan, Huali & Jiang, Guozhang & Li, Gongfa, 2017. "A simulation-based study of dispatching rules in a dynamic job shop scheduling problem with batch release and extended technical precedence constraints," European Journal of Operational Research, Elsevier, vol. 257(1), pages 13-24.

    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. Holthaus, Oliver & Rajendran, Chandrasekharan, 1997. "Efficient dispatching rules for scheduling in a job shop," International Journal of Production Economics, Elsevier, vol. 48(1), pages 87-105, January.
    2. Jayamohan, M. S. & Rajendran, Chandrasekharan, 2004. "Development and analysis of cost-based dispatching rules for job shop scheduling," European Journal of Operational Research, Elsevier, vol. 157(2), pages 307-321, September.
    3. Ferreira, Cristiane & Figueira, Gonçalo & Amorim, Pedro, 2022. "Effective and interpretable dispatching rules for dynamic job shops via guided empirical learning," Omega, Elsevier, vol. 111(C).
    4. Vinod, V. & Sridharan, R., 2011. "Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system," International Journal of Production Economics, Elsevier, vol. 129(1), pages 127-146, January.
    5. Alvarez-Valdes, R. & Fuertes, A. & Tamarit, J. M. & Gimenez, G. & Ramos, R., 2005. "A heuristic to schedule flexible job-shop in a glass factory," European Journal of Operational Research, Elsevier, vol. 165(2), pages 525-534, September.
    6. Yannik Zeiträg & José Rui Figueira, 2023. "Automatically evolving preference-based dispatching rules for multi-objective job shop scheduling," Journal of Scheduling, Springer, vol. 26(3), pages 289-314, June.
    7. Zhang, Rui & Chang, Pei-Chann & Wu, Cheng, 2013. "A hybrid genetic algorithm for the job shop scheduling problem with practical considerations for manufacturing costs: Investigations motivated by vehicle production," International Journal of Production Economics, Elsevier, vol. 145(1), pages 38-52.
    8. Kasper, T.A. Arno & Land, Martin J. & Teunter, Ruud H., 2023. "Towards System State Dispatching in High‐Variety Manufacturing," Omega, Elsevier, vol. 114(C).
    9. 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.
    10. Xiong, Hegen & Fan, Huali & Jiang, Guozhang & Li, Gongfa, 2017. "A simulation-based study of dispatching rules in a dynamic job shop scheduling problem with batch release and extended technical precedence constraints," European Journal of Operational Research, Elsevier, vol. 257(1), pages 13-24.
    11. Sarper, H. & Henry, M. C., 1996. "Combinatorial evaluation of six dispatching rules in a dynamic two-machine flow shop," Omega, Elsevier, vol. 24(1), pages 73-81, February.
    12. Li, Heng & Li, Zhicheng & Li, Ling X. & Hu, Bin, 2000. "A production rescheduling expert simulation system," European Journal of Operational Research, Elsevier, vol. 124(2), pages 283-293, July.
    13. Branke, Juergen & Pickardt, Christoph W., 2011. "Evolutionary search for difficult problem instances to support the design of job shop dispatching rules," European Journal of Operational Research, Elsevier, vol. 212(1), pages 22-32, July.
    14. Zhou, Hong & Cheung, Waiman & Leung, Lawrence C., 2009. "Minimizing weighted tardiness of job-shop scheduling using a hybrid genetic algorithm," European Journal of Operational Research, Elsevier, vol. 194(3), pages 637-649, May.
    15. Amaral Armentano, Vinicius & Rigao Scrich, Cintia, 2000. "Tabu search for minimizing total tardiness in a job shop," International Journal of Production Economics, Elsevier, vol. 63(2), pages 131-140, January.
    16. Ouenniche, J. & Bertrand, J. W. M., 2001. "The finite horizon economic lot sizing problem in job shops: : the multiple cycle approach," International Journal of Production Economics, Elsevier, vol. 74(1-3), pages 49-61, December.
    17. Pickardt, Christoph W. & Hildebrandt, Torsten & Branke, Jürgen & Heger, Jens & Scholz-Reiter, Bernd, 2013. "Evolutionary generation of dispatching rule sets for complex dynamic scheduling problems," International Journal of Production Economics, Elsevier, vol. 145(1), pages 67-77.
    18. Seifert, Ralf W. & Morito, Susumu, 2001. "Cooperative dispatching - exploiting the flexibility of an FMS by means of incremental optimization," European Journal of Operational Research, Elsevier, vol. 129(1), pages 116-133, February.
    19. Halkos, George & Kevork, Ilias, 2002. "Confidence intervals in stationary autocorrelated time series," MPRA Paper 31840, University Library of Munich, Germany.
    20. Sabuncuoglu, Ihsan & Lejmi, Tahar, 1999. "Scheduling for non regular performance measure under the due window approach," Omega, Elsevier, vol. 27(5), pages 555-568, October.

    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:proeco:v:141:y:2013:i:1:p:360-365. 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/ijpe .

    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.