The Mathematical Model for Location-Routing Problem of Relief Logistics Considering the Types of People Under Conditions of Uncertainty

Document Type : Research/ Original/ Regular Article

Authors

1 Department of industrial engineering, Aliabad katoul, Branch, Islamic Azad university, Aliabad katoul, Iran;

2 Department of industrial engineering, Bonab Branch, Islamic Azad university, Bonab, Iran

3 Department of Mathematics, Aliabad katoul, Branch, Islamic Azad university, Aliabad katoul, Iran

Abstract

Crisis management holds significant importance during the occurrence of disasters to ensure  maximum reduction in damages and casualties. From a crisis management perspective, emergency logistics occupy a special position because swift transportation of relief personnel and necessary supplies to the affected area, as well as the evacuation of the injured and others during and after a disaster, are amongst the critical needs. This research addresses the locating, routing, and        distribution of emergency supplies in the context of earthquakes. Objectives of this research include maximizing the probability of successfully navigating routes, minimizing emergency response costs, and reducing discrepancies in the allocation of relief personnel to affected regions. The proposed mathematical model, enhanced with an augmented epsilon constraint approach, has been solved using the GAMS software for a case study of Tehran's 11th district. The consideration of various types of injured individuals, including those with minor injuries and those in critical condition, as well as the homeless and relief workers in a concurrent manner, and the development of a three-objective, multi-commodity, multi-vehicle mathematical model with scenarios incorporating uncertainty, are among the innovations of this study.
 

Keywords

Main Subjects

Smiley face

References

  1. [1] G. de Castro Pena, A. C. Santos, and C. Prins, "Solving the integrated multi-period scheduling routing problem for cleaning debris in the aftermath of disasters," European Journal of Operational Research, vol. 306, no. 1, pp. 156-172, 2023/04/01/ https://doi.org/10.1016/j.ejor.2022.07.005

    [2] M. Tavana, A.-R. Abtahi, D. D. Caprio, R. Hashemi, and R. Y. Zenouz, "An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations," Socio-Economic Planning Sciences, vol. 64, pp. 21-37, 2018 https://doi.org/10.1016/j.seps.2017.12.004

    [3] A. M. Afshar, "A mathematical framework for optimizing disaster relief logistics," Thesis for Degree Doctor of Philosophy, Department of Civil and Environmental Engineering, University of Maryland, 2011.

    [4] C. Cao, Y. Liu, O. Tang, and X. Gao, "A fuzzy bi-level optimization model for multi-period post-disaster relief distribution in sustainable humanitarian supply chains," International Journal of Production Economics, vol. 235, p. 108081. https://doi.org/10.1016/j.ijpe.2021.108081

    [5] I. Shokr, F. Jolai, and A. Bozorgi-Amiri, "A novel humanitarian and private sector relief chain network design model for disaster response," International Journal of Disaster Risk Reduction, vol. 65, p. 102522, 2021/11/01/ 2021. https://doi.org/10.1016/j.ijdrr.2021.102522.

    [6] S. Mohammadi, S. Avakh Darestani, B. Vahdani, and A. Alinezhad, "A robust neutrosophic fuzzy-based approach to integrate reliable facility location and routing decisions for disaster relief under fairness and aftershocks concerns," Computers & Industrial Engineering, vol. 148, p. 106734, 2020/10/01/ 2020. https://doi.org/10.1016/j.cie.2020.106734.

    [7] B. Rabta, C. Wankmüller, and G. Reiner, "A drone fleet model for last-mile distribution in disaster relief operations," International Journal of Disaster Risk Reduction, vol. 28, pp. 107-112, 2018/06/01/ 2018. https://doi.org/10.1016/j.ijdrr.2018.02.020.

    1. Ali Torabi, I. Shokr, S. Tofighi, and J. [8] Heydari, "Integrated relief pre-positioning and procurement planning in humanitarian supply chains," Transportation Research Part E: Logistics and Transportation Review, vol. 113, pp. 123-146, 2018/05/01/ 2018. https://doi.org/10.1016/j.tre.2018.03

    [9] P. Ghasemi, F. Goodarzian, and A. Abraham, "A new humanitarian relief logistic network for multi-objective optimization under stochastic programming," Applied Intelligence, vol. 52, no. 12, pp. 13729-13762, 2022/09/01 2022. https:// doi: 10.1007/s10489-0

    [10] C. Toregas, R. Swain, C. ReVelle, and L. Bergman, "The Location of Emergency Service Facilities," Operation Research, vol. 19, no. 6, pp. 1363-1373, 1971. https://doi.org/10.1287/opre.19.6.1363.

    [11] W. Yi and L. Özdamar, "A dynamic logistics coordination model for evacuation and support in disaster response activities," European Journal of Operational Research, vol. 179, no. 3, pp. 1177-1193, 2007, doi: 10.1016/j.ejor.2005.03.077.

    [12] A. Afshar and A. Haghani, "Modeling integrated supply chain logistics in real-time large-scale disaster relief operations," Socio-Economic Planning Sciences vol. 46, no. 4, pp. 327-338, 2012, doi: 10.1016/j.seps.2011.12.003.

    [13] A. BozorgiAmiri, M. S. Jabalameli, M. Alinaghian, and M. Heydari, "A modified particle swarm optimization for disaster relief logistics under uncertain environment," The International Journal of Advanced Manufacturing Technology, vol. 60, no. 1-4, pp. 357-371, 2012, doi: 10.1007/s00170-011-3596-8.

    [14] J. A. Paul and G. Hariharan, "Location-allocation planning of stockpiles for effective disaster mitigation," Annals of Operations Research, vol. 196, no. 1, pp. 469-490, 2012, doi: 10.1007/s10479-011-1052-7.

    [15] R. Abounacer, M. Rekik, and J. Renaud, "An exact solution approach for multi-objective location–transportation problem for disaster response," Computers & Operations Research, vol. 41, pp. 83-93, 2014, doi: 10.1016/j.cor.2013.08.001.

    [16] H. Wang, L. Du, and S. Ma, "Multi-objective open location-routing model with split delivery for optimized relief distribution in post-earthquake," Transportation Research Part E, vol. 69, pp. 160-179, 2014, doi: 10.1016/j.tre.2014.06.006.

    [17] M. Ahmadi, A. Seifi, and B. Tootooni, "A humanitarian logistics model for disaster relief operation considering network failure and standard relief time: A case study on San Francisco district," Transportation Research Part E: Logistics and Transportation Review, vol. 75, pp. 145-163, 2015, doi: 10.1016/j.tre.2015.01.008.

    [18] B. Vahdani, D. Veysmoradi, F. Noori, and F. Mansour, "Two-stage multi-objective location-routing-inventory model for humanitarian logistics network design under uncertainty," International Journal of Disaster Risk Reduction, vol. 27, pp.   290-306, 2018. https://doi.org/10.1016/j.ijdrr.2017.10.015.

    [19] D. Veysmoradi, B. Vahdani, M. F. Sartangi, and S. M. Mousavi, "Multi-objective open location-routing model for relief distribution networks with split delivery and multi-mode transportation under uncertainty," Scientia Iranica E: Industrial engineering, vol. 25, no. 6, pp. 3635-3653, 2018.

    [20] P. Ghasemi, K. Khalili-Damghani, A. Hafezalkotob, and S. Raissi, "Uncertain multi-objective multi-commodity multi-period multi-vehicle location-allocation model for earthquake evacuation planning," Applied Mathematics and Computation, vol. 350, pp. 105-132, 2019. https://doi.org/10.1016/j.amc.2018.12.061

    [21] F. Faghih-Mohammadi, M. Nasiri, D. Konur." Cross-dock facility for disaster relief operations", Annals of Operations Research, vol. 322, pp. 497-538, 2023 . https://doi.org/10.1007/s10479-022-04939-2

Files

History

  • Receive Date: 15 October 2023
  • Revise Date: 21 December 2023
  • Accept Date: 06 February 2024
  • Publish Date: 20 May 2024

Share

How to cite

Statistics