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Pre-positioning of relief items in humanitarian logistics considering lateral transhipment opportunities

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  • Baskaya, Serhat
  • Ertem, Mustafa Alp
  • Duran, Serhan

Abstract

The main objective of this study is to investigate the inclusion of lateral transhipment opportunities into the humanitarian relief chain and to examine the effect of different parameters on minimizing the average distance travelled per item while serving the beneficiaries. Direct shipment model (DT), lateral transhipment model (LTSP) and maritime lateral transhipment model (MLTSP) are developed and compared between each other by using a real life earthquake scenario prepared for the city of Istanbul by JICA (Japanese International Cooperation Agency). Developed mathematical models decide on the locations and number of disaster relief facilities, quantity of relief items to hold at those facilities, and quantity of lateral transhipment between the facilities. Vulnerability of the roads and heterogeneous capacitated facilities are also considered. It can be concluded that both LTSP and MLTSP models gave better results than DT model and lateral transhipment option helps beneficiaries to obtain relief items faster and with higher service level.

Suggested Citation

  • Baskaya, Serhat & Ertem, Mustafa Alp & Duran, Serhan, 2017. "Pre-positioning of relief items in humanitarian logistics considering lateral transhipment opportunities," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 50-60.
    • Handle: RePEc:eee:soceps:v:57:y:2017:i:c:p:50-60
    DOI: 10.1016/j.seps.2016.09.001
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    5. Tavana, Madjid & Abtahi, Amir-Reza & Di Caprio, Debora & Hashemi, Reza & Yousefi-Zenouz, Reza, 2018. "An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations," Socio-Economic Planning Sciences, Elsevier, vol. 64(C), pages 21-37.
    6. Yusen Ye & Wen Jiao & Hong Yan, 2020. "Managing Relief Inventories Responding to Natural Disasters: Gaps Between Practice and Literature," Production and Operations Management, Production and Operations Management Society, vol. 29(4), pages 807-832, April.
    7. Hu, Shaolong & Han, Chuanfeng & Dong, Zhijie Sasha & Meng, Lingpeng, 2019. "A multi-stage stochastic programming model for relief distribution considering the state of road network," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 64-87.
    8. Sabbaghtorkan, Monir & Batta, Rajan & He, Qing, 2020. "Prepositioning of assets and supplies in disaster operations management: Review and research gap identification," European Journal of Operational Research, Elsevier, vol. 284(1), pages 1-19.
    9. Aghajani, Mojtaba & Ali Torabi, S. & Altay, Nezih, 2023. "Resilient relief supply planning using an integrated procurement-warehousing model under supply disruption," Omega, Elsevier, vol. 118(C).
    10. Zohaib Hassan & Irtiza Ali Shah & Ahsan Sarwar Rana, 2022. "Charging Stations Distribution Optimization using Drones Fleet for Disaster Prone Areas," International Journal of Innovations in Science & Technology, 50sea, vol. 4(5), pages 103-121, June.
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