IDEAS home Printed from https://ideas.repec.org/a/igg/jban00/v8y2021i2p63-82.html
   My bibliography  Save this article

A Humanitarian Green Supply Chain Management Considering Minimum Cost and Time

Author

Listed:
  • Dipanjana Sengupta

    (National Institute of Technology, Agartala, India)

  • Amrit Das

    (Vellore Institute of Technology, India)

  • Uttam Kumar Bera

    (National Institute of Technology, Agartala, India)

  • Anirban Dutta

    (National Institute of Technology, Agartala, India)

Abstract

Disaster is the sudden problem of the world. There is no time bound. By disaster, all the creatures of the earth are affected. Here, the authors have tried to show some issues which are related to the natural calamities and green transportation. The main investigation of the paper is to describe about humanitarian supply chain management with optimized transportation cost, time, and carbon emission. Here a real-life problem of flood affected area has been chosen. When such disasters happen, quick response can reduce the devastation and save lives, and thus, it requires fulfilling the basic humanitarian needs of the affected population. In such case, organizations should also maintain the emission of the vehicles in safe range to mitigate the further disaster by pollution. A multi-objective solid transportation problem considering cost, time, and emission has been presented here. To solve the problem, this paper has used goal programming method and pareto optimal solution method. A comparison of results is also shown later. Some managerial insights are drawn to describe the situation.

Suggested Citation

  • Dipanjana Sengupta & Amrit Das & Uttam Kumar Bera & Anirban Dutta, 2021. "A Humanitarian Green Supply Chain Management Considering Minimum Cost and Time," International Journal of Business Analytics (IJBAN), IGI Global, vol. 8(2), pages 63-82, April.
    • Handle: RePEc:igg:jban00:v:8:y:2021:i:2:p:63-82
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJBAN.2021040105
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Singh, Bikramjit & Singh, Amarinder, 2023. "Hybrid particle swarm optimization for pure integer linear solid transportation problem," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 207(C), pages 243-266.
    2. Amrit Das & Gyu M. Lee, 2021. "A Multi-Objective Stochastic Solid Transportation Problem with the Supply, Demand, and Conveyance Capacity Following the Weibull Distribution," Mathematics, MDPI, vol. 9(15), pages 1-21, July.

    More about this item

    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:igg:jban00:v:8:y:2021:i:2:p:63-82. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.