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Multiresource Allocation Scheduling in Dynamic Environments

Author

Listed:
  • Woonghee Tim Huh

    (Sauder School of Business, University of British Columbia, Vancouver, British Columbia V6T 1Z2, Canada)

  • Nan Liu

    (Department of Health Policy and Management, Mailman School of Public Health, Columbia University, New York, New York 10032)

  • Van-Anh Truong

    (Department of Industrial Engineering and Operations Research, Columbia University, New York, New York 10027)

Abstract

Motivated by service capacity-management problems in healthcare contexts, we consider a multiresource allocation problem with two classes of jobs (elective and emergency) in a dynamic and nonstationary environment. Emergency jobs need to be served immediately, whereas elective jobs can wait. Distributional information about demand and resource availability is continually updated, and we allow jobs to renege. We prove that our formulation is convex, and the optimal amount of capacity reserved for emergency jobs in each period decreases with the number of elective jobs waiting for service. However, the optimal policy is difficult to compute exactly. We develop the idea of a limit policy starting at a particular time, and use this policy to obtain upper and lower bounds on the decisions of an optimal policy in each period, and also to develop several computationally efficient policies. We show in computational experiments that our best policy performs within 1.8% of an optimal policy on average.

Suggested Citation

  • Woonghee Tim Huh & Nan Liu & Van-Anh Truong, 2013. "Multiresource Allocation Scheduling in Dynamic Environments," Manufacturing & Service Operations Management, INFORMS, vol. 15(2), pages 280-291, May.
    • Handle: RePEc:inm:ormsom:v:15:y:2013:i:2:p:280-291
    DOI: 10.1287/msom.1120.0415
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    References listed on IDEAS

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