IDEAS home Printed from https://ideas.repec.org/a/inm/orijoc/v34y2022i5p2389-2399.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/ijoc.2022.1204
    Download Restriction: no
    File URL: https://libkey.io/10.1287/ijoc.2022.1204?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
    ---><---

    References listed on IDEAS

    as
    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. Huang, Michael & Smilowitz, Karen & Balcik, Burcu, 2012. "Models for relief routing: Equity, efficiency and efficacy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 2-18.
    4. 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.
    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. 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.

    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. Cao, Cejun & Liu, Yang & Tang, Ou & Gao, Xuehong, 2021. "A fuzzy bi-level optimization model for multi-period post-disaster relief distribution in sustainable humanitarian supply chains," International Journal of Production Economics, Elsevier, vol. 235(C).
    2. Yichen Lu & Chao Yang & Jun Yang, 2022. "A multi-objective humanitarian pickup and delivery vehicle routing problem with drones," Annals of Operations Research, Springer, vol. 319(1), pages 291-353, December.
    3. A. Anaya-Arenas & J. Renaud & A. Ruiz, 2014. "Relief distribution networks: a systematic review," Annals of Operations Research, Springer, vol. 223(1), pages 53-79, December.
    4. Karsu, Özlem & Morton, Alec, 2015. "Inequity averse optimization in operational research," European Journal of Operational Research, Elsevier, vol. 245(2), pages 343-359.
    5. Omid Shahvari & Rasaratnam Logendran & Madjid Tavana, 2022. "An efficient model-based branch-and-price algorithm for unrelated-parallel machine batching and scheduling problems," Journal of Scheduling, Springer, vol. 25(5), pages 589-621, October.
    6. Dilsu Binnaz Ozkapici & Mustafa Alp Ertem & Haluk Aygüneş, 2016. "Intermodal humanitarian logistics model based on maritime transportation in Istanbul," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(1), pages 345-364, August.
    7. Changshi Liu & Gang Kou & Yi Peng & Fawaz E. Alsaadi, 2019. "Location-Routing Problem for Relief Distribution in the Early Post-Earthquake Stage from the Perspective of Fairness," Sustainability, MDPI, vol. 11(12), pages 1-16, June.
    8. Chen, Xinwei & Wang, Tong & Thomas, Barrett W. & Ulmer, Marlin W., 2023. "Same-day delivery with fair customer service," European Journal of Operational Research, Elsevier, vol. 308(2), pages 738-751.
    9. Sperling, Martina & Schryen, Guido, 2022. "Decision support for disaster relief: Coordinating spontaneous volunteers," European Journal of Operational Research, Elsevier, vol. 299(2), pages 690-705.
    10. Fan, Yu & Shao, Jianfang & Wang, Xihui & Liang, Liang, 2024. "Contract design between relief organisations and private-sector vendors: A humanitarian logistics framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    11. Sha-lei Zhan & Nan Liu & Yong Ye, 2014. "Coordinating efficiency and equity in disaster relief logistics via information updates," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(8), pages 1607-1621, August.
    12. Li Zhu & Yeming Gong & Yishui Xu & Jun Gu, 2019. "Emergency Relief Routing Models for Injured Victims Considering Equity and Priority," Post-Print hal-02879681, HAL.
    13. Ferrer, José M. & Martín-Campo, F. Javier & Ortuño, M. Teresa & Pedraza-Martínez, Alfonso J. & Tirado, Gregorio & Vitoriano, Begoña, 2018. "Multi-criteria optimization for last mile distribution of disaster relief aid: Test cases and applications," European Journal of Operational Research, Elsevier, vol. 269(2), pages 501-515.
    14. Yan Li & Xiao Xu & Fuyu Wang, 2023. "Research on Home Health Care Scheduling Considering Synchronous Access of Caregivers and Vehicles," Sustainability, MDPI, vol. 15(7), pages 1-18, April.
    15. Jeong, Ho Young & Yu, David J. & Min, Byung-Cheol & Lee, Seokcheon, 2020. "The humanitarian flying warehouse," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    16. Wu, Lingxiao & Wang, Shuaian, 2018. "Exact and heuristic methods to solve the parallel machine scheduling problem with multi-processor tasks," International Journal of Production Economics, Elsevier, vol. 201(C), pages 26-40.
    17. Goerigk, Marc & Deghdak, Kaouthar & Heßler, Philipp, 2014. "A comprehensive evacuation planning model and genetic solution algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 82-97.
    18. Esteban Ogazón & Neale R. Smith & Angel Ruiz, 2022. "Reconfiguration of Foodbank Network Logistics to Cope with a Sudden Disaster," Mathematics, MDPI, vol. 10(9), pages 1-20, April.
    19. Hewitt, Mike & Nowak, Maciek & Gala, Leo, 2015. "Consolidating home meal delivery with limited operational disruption," European Journal of Operational Research, Elsevier, vol. 243(1), pages 281-291.
    20. Ferreira, Cristiane & Figueira, Gonçalo & Amorim, Pedro, 2021. "Scheduling Human-Robot Teams in collaborative working cells," International Journal of Production Economics, Elsevier, vol. 235(C).

    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:inm:orijoc:v:34:y:2022:i:5:p:2389-2399. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.