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A multi-objective stochastic programming model to configure a sustainable humanitarian logistics considering deprivation cost and patient severity

Author

Listed:
  • Amir Jamali

    (University of Tehran)

  • Amirhossein Ranjbar

    (University of Tehran)

  • Jafar Heydari

    (University of Tehran)

  • Sina Nayeri

    (University of Tehran)

Abstract

As the occurrence of disasters has increased frequently and has resulted in growing concern about their adverse effects on the environment, Sustainable Humanitarian Logistics (SHL) has received great attention recently. SHL aims to reduce disaster damages in an environmentally-friendly manner in the shortest possible time. The terms including ‘environmentally-friendly’ and ‘shortest possible time’ refer to the environmental and social aspects of sustainability. This research proposes a stochastic multi-objective mixed-integer programming model to configure an SHL network during the response phase. Having compared to the research literature, this is the first study that considers economic, social, and environmental aspects of sustainability by incorporating relief cost, deprivation cost, and carbon emissions, respectively. Then, the improved multi-choice goal programming approach is applied to solve the proposed multi-objective model. To indicate the validity of the proposed model, an earthquake that occurred in a region of Kermanshah, Iran, in 2017 is investigated as a real case study. Finally, sensitivity analysis is performed and several managerial and theoretical insights are provided. The results show that exerting environmental issues in humanitarian logistics does not necessarily increase the relief costs, but can be in contrast with the social aspect. Furthermore, a minor increase in the budget of the preparedness phase drastically decreases the response costs.

Suggested Citation

  • Amir Jamali & Amirhossein Ranjbar & Jafar Heydari & Sina Nayeri, 2022. "A multi-objective stochastic programming model to configure a sustainable humanitarian logistics considering deprivation cost and patient severity," Annals of Operations Research, Springer, vol. 319(1), pages 1265-1300, December.
    • Handle: RePEc:spr:annopr:v:319:y:2022:i:1:d:10.1007_s10479-021-04014-2
    DOI: 10.1007/s10479-021-04014-2
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    1. Ruth Banomyong & Paitoon Varadejsatitwong & Richard Oloruntoba, 2019. "A systematic review of humanitarian operations, humanitarian logistics and humanitarian supply chain performance literature 2005 to 2016," Annals of Operations Research, Springer, vol. 283(1), pages 71-86, December.
    2. Angappa Gunasekaran & Rameshwar Dubey & Samuel Fosso Wamba & Thanos Papadopoulos & Benjamin T. Hazen & Eric W.T. Ngai, 2018. "Bridging humanitarian operations management and organisational theory," International Journal of Production Research, Taylor & Francis Journals, vol. 56(21), pages 6735-6740, November.
    3. Rameshwar Dubey & Angappa Gunasekaran & David J. Bryde & Yogesh K. Dwivedi & Thanos Papadopoulos, 2020. "Blockchain technology for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting," International Journal of Production Research, Taylor & Francis Journals, vol. 58(11), pages 3381-3398, June.
    4. A. Charnes & W. W. Cooper & R. O. Ferguson, 1955. "Optimal Estimation of Executive Compensation by Linear Programming," Management Science, INFORMS, vol. 1(2), pages 138-151, January.
    5. Shaoqing Geng & Hanping Hou & Shaoguang Zhang, 2020. "Multi-Criteria Location Model of Emergency Shelters in Humanitarian Logistics," Sustainability, MDPI, vol. 12(5), pages 1-21, February.
    6. Aghajani, Mojtaba & Torabi, S. Ali & Heydari, Jafar, 2020. "A novel option contract integrated with supplier selection and inventory prepositioning for humanitarian relief supply chains," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    7. Ali Ekici & Okan Örsan Özener, 2020. "Inventory routing for the last mile delivery of humanitarian relief supplies," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(3), pages 621-660, September.
    8. Xihui Wang & Xiang Wang & Liang Liang & Xiaohang Yue & Luk N. Van Wassenhove, 2017. "Estimation of Deprivation Level Functions using a Numerical Rating Scale," Production and Operations Management, Production and Operations Management Society, vol. 26(11), pages 2137-2150, November.
    9. Clay Whybark, D., 2007. "Issues in managing disaster relief inventories," International Journal of Production Economics, Elsevier, vol. 108(1-2), pages 228-235, July.
    10. M. Ülkü & Kathryn Bell & Stephanie Wilson, 2015. "Modeling the impact of donor behavior on humanitarian aid operations," Annals of Operations Research, Springer, vol. 230(1), pages 153-168, July.
    11. Macea, Luis F. & Cantillo, Victor & Arellana, Julian, 2018. "Influence of attitudes and perceptions on deprivation cost functions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 112(C), pages 125-141.
    12. Altay, Nezih & Green III, Walter G., 2006. "OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 175(1), pages 475-493, November.
    13. Rameshwar Dubey & Angappa Gunasekaran & Thanos Papadopoulos, 2019. "Disaster relief operations: past, present and future," Annals of Operations Research, Springer, vol. 283(1), pages 1-8, December.
    14. Raghuram G. Rajan & Arvind Subramanian, 2008. "Aid and Growth: What Does the Cross-Country Evidence Really Show?," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 643-665, November.
    15. Amy Givler Chapman & John E. Mitchell, 2018. "A fair division approach to humanitarian logistics inspired by conditional value-at-risk," Annals of Operations Research, Springer, vol. 262(1), pages 133-151, March.
    16. Wilfredo Yushimito & Miguel Jaller & Satish Ukkusuri, 2012. "A Voronoi-Based Heuristic Algorithm for Locating Distribution Centers in Disasters," Networks and Spatial Economics, Springer, vol. 12(1), pages 21-39, March.
    17. Milad Keshvari Fard & Mahyar Eftekhar & Felix Papier, 2019. "An Approach for Managing Operating Assets for Humanitarian Development Programs," Production and Operations Management, Production and Operations Management Society, vol. 28(8), pages 2132-2151, August.
    18. Cejun Cao & Congdong Li & Qin Yang & Fanshun Zhang, 2017. "Multi-Objective Optimization Model of Emergency Organization Allocation for Sustainable Disaster Supply Chain," Sustainability, MDPI, vol. 9(11), pages 1-22, November.
    19. Charbel José Chiappetta Jabbour & Vinicius Amorim Sobreiro & Ana Beatriz Lopes de Sousa Jabbour & Lucila Maria Souza Campos & Enzo Barberio Mariano & Douglas William Scott Renwick, 2019. "An analysis of the literature on humanitarian logistics and supply chain management: paving the way for future studies," Annals of Operations Research, Springer, vol. 283(1), pages 289-307, December.
    20. Tofighi, S. & Torabi, S.A. & Mansouri, S.A., 2016. "Humanitarian logistics network design under mixed uncertainty," European Journal of Operational Research, Elsevier, vol. 250(1), pages 239-250.
    21. Cotes, Nathalie & Cantillo, Victor, 2019. "Including deprivation costs in facility location models for humanitarian relief logistics," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 89-100.
    22. Gutjahr, Walter J. & Fischer, Sophie, 2018. "Equity and deprivation costs in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 270(1), pages 185-197.
    23. Delgado-Lindeman, Maira & Arellana, Julián & Cantillo, Víctor, 2019. "Willingness to pay functions for emergency ambulance services," Journal of choice modelling, Elsevier, vol. 30(C), pages 28-37.
    24. Daria Battini & Umberto Peretti & Alessandro Persona & Fabio Sgarbossa, 2016. "Sustainable humanitarian operations: closed-loop supply chain," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 25(1), pages 65-79.
    25. Balcik, Burcu & Yanıkoğlu, İhsan, 2020. "A robust optimization approach for humanitarian needs assessment planning under travel time uncertainty," European Journal of Operational Research, Elsevier, vol. 282(1), pages 40-57.
    26. Behl, Abhishek & Dutta, Pankaj, 2020. "Engaging donors on crowdfunding platform in Disaster Relief Operations (DRO) using gamification: A Civic Voluntary Model (CVM) approach," International Journal of Information Management, Elsevier, vol. 54(C).
    27. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Roubaud, David & Fosso Wamba, Samuel & Giannakis, Mihalis & Foropon, Cyril, 2019. "Big data analytics and organizational culture as complements to swift trust and collaborative performance in the humanitarian supply chain," International Journal of Production Economics, Elsevier, vol. 210(C), pages 120-136.
    28. Cantillo, Victor & Serrano, Iván & Macea, Luis F. & Holguín-Veras, José, 2018. "Discrete choice approach for assessing deprivation cost in humanitarian relief operations," Socio-Economic Planning Sciences, Elsevier, vol. 63(C), pages 33-46.
    29. Rivera-Royero, Daniel & Galindo, Gina & Yie-Pinedo, Ruben, 2016. "A dynamic model for disaster response considering prioritized demand points," Socio-Economic Planning Sciences, Elsevier, vol. 55(C), pages 59-75.
    30. Paul, Jomon A. & Zhang, Minjiao, 2019. "Supply location and transportation planning for hurricanes: A two-stage stochastic programming framework," European Journal of Operational Research, Elsevier, vol. 274(1), pages 108-125.
    31. Rameshwar Dubey & Nezih Altay & Constantin Blome, 2019. "Swift trust and commitment: The missing links for humanitarian supply chain coordination?," Annals of Operations Research, Springer, vol. 283(1), pages 159-177, December.
    32. Abhishek Behl & Pankaj Dutta, 2019. "Humanitarian supply chain management: a thematic literature review and future directions of research," Annals of Operations Research, Springer, vol. 283(1), pages 1001-1044, December.
    33. Kelle, Peter & Schneider, Helmut & Yi, Huizhi, 2014. "Decision alternatives between expected cost minimization and worst case scenario in emergency supply – Second revision," International Journal of Production Economics, Elsevier, vol. 157(C), pages 250-260.
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