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Heterogeneous Multi-resource Allocation with Subset Demand Requests

Author

Listed:
  • Arden Baxter

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332; Center for Health and Humanitarian Systems, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Pinar Keskinocak

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332; Center for Health and Humanitarian Systems, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Mohit Singh

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

Abstract

We consider the problem of allocating multiple heterogeneous resources geographically and over time to meet demands that require some subset of the available resource types simultaneously at a specified time, location, and duration. The objective is to maximize the total reward accrued from meeting (a subset of) demands. We model this problem as an integer program, show that it is NP-hard, and analyze the complexity of various special cases. We introduce approximation algorithms and an extension to our problem that considers travel costs. Finally, we test the performance of the integer programming model in an extensive computational study.

Suggested Citation

  • Arden Baxter & Pinar Keskinocak & Mohit Singh, 2022. "Heterogeneous Multi-resource Allocation with Subset Demand Requests," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2389-2399, September.
    • Handle: RePEc:inm:orijoc:v:34:y:2022:i:5:p:2389-2399
    DOI: 10.1287/ijoc.2022.1204
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    References listed on IDEAS

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    1. Jianer Chen & Chung‐Yee Lee, 1999. "General multiprocessor task scheduling," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(1), pages 57-74, February.
    2. Rauchecker, Gerhard & Schryen, Guido, 2019. "An exact branch-and-price algorithm for scheduling rescue units during disaster response," European Journal of Operational Research, Elsevier, vol. 272(1), pages 352-363.
    3. Hossein Hashemi Doulabi & Gilles Pesant & Louis-Martin Rousseau, 2020. "Vehicle Routing Problems with Synchronized Visits and Stochastic Travel and Service Times: Applications in Healthcare," Transportation Science, INFORMS, vol. 54(4), pages 1053-1072, July.
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    Cited by:

    1. Arden Baxter & Pinar Keskinocak & Mohit Singh, 2023. "Heterogeneous Multi-resource Planning and Allocation Under Stochastic Demand," INFORMS Journal on Computing, INFORMS, vol. 35(5), pages 929-951, September.

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