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An approximate dynamic programing approach to the development of heuristics for the scheduling of impatient jobs in a clearing system

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  • Dong Li
  • Kevin D. Glazebrook

Abstract

A single server is faced with a collection of jobs of varying duration and urgency. Each job has a random lifetime during which it is available for nonpreemptive service. Should a job's lifetime expire before its service begins then it is lost from the system unserved. The goal is to schedule the jobs for service to maximize the expected number served to completion. Two heuristics have been proposed in the literature. One (labeled πS) operates a static priority among the job classes and works well in a “no premature job loss” limit, whereas the second (πM) is a myopic heuristic which works well when lifetimes are short. Both can exhibit poor performance for problems at some distance from the regimes for which they were designed. We develop a robustly good heuristic by an approximative approach to the application of a policy improvement step to the asymptotically optimal heuristic πS, in which we use a fluid model to obtain an approximation for the value function of πS. The performance of the proposed heuristic is investigated in an extensive numerical study. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010

Suggested Citation

  • Dong Li & Kevin D. Glazebrook, 2010. "An approximate dynamic programing approach to the development of heuristics for the scheduling of impatient jobs in a clearing system," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(3), pages 225-236, April.
    • Handle: RePEc:wly:navres:v:57:y:2010:i:3:p:225-236
    DOI: 10.1002/nav.20395
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    References listed on IDEAS

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    1. Michelle Opp & Kevin Glazebrook & Vidyadhar G. Kulkarni, 2005. "Outsourcing warranty repairs: Dynamic allocation," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(5), pages 381-398, August.
    2. K. D. Glazebrook & C. Kirkbride & J. Ouenniche, 2009. "Index Policies for the Admission Control and Routing of Impatient Customers to Heterogeneous Service Stations," Operations Research, INFORMS, vol. 57(4), pages 975-989, August.
    3. Jan A. Van Mieghem, 2003. "Due-Date Scheduling: Asymptotic Optimality of Generalized Longest Queue and Generalized Largest Delay Rules," Operations Research, INFORMS, vol. 51(1), pages 113-122, February.
    4. Ger Koole, 2008. "Introduction to the Special Issue on Call Center Management," Management Science, INFORMS, vol. 54(2), pages 237-237, February.
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    Cited by:

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    2. Dong Li & Li Ding & Stephen Connor, 2020. "When to Switch? Index Policies for Resource Scheduling in Emergency Response," Production and Operations Management, Production and Operations Management Society, vol. 29(2), pages 241-262, February.
    3. Rezapour, Shabnam & Naderi, Nazanin & Morshedlou, Nazanin & Rezapourbehnagh, Shaghayegh, 2018. "Optimal deployment of emergency resources in sudden onset disasters," International Journal of Production Economics, Elsevier, vol. 204(C), pages 365-382.
    4. Yisha Xiang & Jun Zhuang, 2016. "A medical resource allocation model for serving emergency victims with deteriorating health conditions," Annals of Operations Research, Springer, vol. 236(1), pages 177-196, January.
    5. Michael N. Katehakis & Benjamin Melamed & Jim Junmin Shi, 2022. "Optimal replenishment rate for inventory systems with compound Poisson demands and lost sales: a direct treatment of time-average cost," Annals of Operations Research, Springer, vol. 317(2), pages 665-691, October.
    6. Farahani, Reza Zanjirani & Lotfi, M.M. & Baghaian, Atefe & Ruiz, Rubén & Rezapour, Shabnam, 2020. "Mass casualty management in disaster scene: A systematic review of OR&MS research in humanitarian operations," European Journal of Operational Research, Elsevier, vol. 287(3), pages 787-819.
    7. Lee, Hyun-Rok & Lee, Taesik, 2021. "Multi-agent reinforcement learning algorithm to solve a partially-observable multi-agent problem in disaster response," European Journal of Operational Research, Elsevier, vol. 291(1), pages 296-308.
    8. Atefe Baghaian & M. M. Lotfi & Shabnam Rezapour, 2022. "Integrated deployment of local urban relief teams in the first hours after mass casualty incidents," Operational Research, Springer, vol. 22(4), pages 4517-4555, September.
    9. Terry James & Kevin Glazebrook & Kyle Lin, 2016. "Developing Effective Service Policies for Multiclass Queues with Abandonment: Asymptotic Optimality and Approximate Policy Improvement," INFORMS Journal on Computing, INFORMS, vol. 28(2), pages 251-264, May.
    10. Liu, Yang & Cui, Na & Zhang, Jianghua, 2019. "Integrated temporary facility location and casualty allocation planning for post-disaster humanitarian medical service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 1-16.
    11. Hyun-Rok Lee & Taesik Lee, 2018. "Markov decision process model for patient admission decision at an emergency department under a surge demand," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 98-122, June.

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