IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v104y2026ics0038012126000200.html

Optimizing medical waste collection in urban systems: A constraint programming approach for sustainable public sector decision-making

Author

Listed:
  • Pham, Hung
  • Le, Tuan
  • Huynh, Nhi
  • Chu, Tuan
  • Pham, Hiep
  • Truong Quang, Huy
  • Dao, Son

Abstract

This study addresses the optimization of medical waste collection (MWC) in Ho Chi Minh City, Vietnam, where increasing waste volumes pose challenges for efficiency and sustainability. Using real-world operational data from Citenco, we formulate the problem as a capacitated vehicle routing problem (CVRP) with stochastic demand, solved through a combination of constraint programming and chance-constrained programming. The proposed model reduces total travel distance by 22%, travel time by 10%, and increases vehicle load utilization by 6%, while lowering the number of daily trips to treatment facilities. Sensitivity analysis confirms robustness under varying service levels and expanded coverage. These results provide evidence-based insights for policymakers and public waste management agencies, supporting sustainable decision-making in urban medical waste collection.

Suggested Citation

  • Pham, Hung & Le, Tuan & Huynh, Nhi & Chu, Tuan & Pham, Hiep & Truong Quang, Huy & Dao, Son, 2026. "Optimizing medical waste collection in urban systems: A constraint programming approach for sustainable public sector decision-making," Socio-Economic Planning Sciences, Elsevier, vol. 104(C).
    • Handle: RePEc:eee:soceps:v:104:y:2026:i:c:s0038012126000200
    DOI: 10.1016/j.seps.2026.102434
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012126000200
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.seps.2026.102434?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:soceps:v:104:y:2026:i:c:s0038012126000200. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/seps .

    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.