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An integrated routing and scheduling model for evacuation and commodity distribution in large-scale disaster relief operations: a case study

Author

Listed:
  • Fatemeh Sabouhi

    (Iran University of Science and Technology)

  • Ali Bozorgi-Amiri

    (University of Tehran)

  • Mohammad Moshref-Javadi

    (Purdue University)

  • Mehdi Heydari

    (Iran University of Science and Technology)

Abstract

Every year natural and man-made disasters cause considerable human and economic losses. It is essential to prepare for different relief operations to prevent and reduce these losses. In this paper, we propose an integrated evacuation and distribution logistic system to obtain simultaneous routing and scheduling of vehicles to evacuate people from affected areas to shelters and provide them with necessary relief commodities. We assume that shelters and vehicles have limited capacity and the demand of each affected area and distribution center could be fulfilled by more than one vehicle (split delivery). The proposed problem is formulated as a Mixed-Integer Linear Programming model with the objective of minimization of the sum of arrival times of the vehicles at affected areas, shelters, and distribution centers. We also propose a Memetic Algorithm (MA) to solve this integrated model on large-scale problems efficiently after tuning the MA parameters using the Taguchi method. The proposed model and algorithm are used to solve a case study in Tehran, the capital of Iran. The evaluation of the results shows the effectiveness of the proposed disaster relief logistic system in minimizing the total waiting time of evacuees and delivery time of supplies. The results also show that the number of relief vehicles and capacity of shelters can considerably affect the total relief time in disaster relief operations.

Suggested Citation

  • Fatemeh Sabouhi & Ali Bozorgi-Amiri & Mohammad Moshref-Javadi & Mehdi Heydari, 2019. "An integrated routing and scheduling model for evacuation and commodity distribution in large-scale disaster relief operations: a case study," Annals of Operations Research, Springer, vol. 283(1), pages 643-677, December.
  • Handle: RePEc:spr:annopr:v:283:y:2019:i:1:d:10.1007_s10479-018-2807-1
    DOI: 10.1007/s10479-018-2807-1
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    1. Safaei, N. & Saidi-Mehrabad, M. & Jabal-Ameli, M.S., 2008. "A hybrid simulated annealing for solving an extended model of dynamic cellular manufacturing system," European Journal of Operational Research, Elsevier, vol. 185(2), pages 563-592, March.
    2. Tzeng, Gwo-Hshiung & Cheng, Hsin-Jung & Huang, Tsung Dow, 2007. "Multi-objective optimal planning for designing relief delivery systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 673-686, November.
    3. Wohlgemuth, Sascha & Oloruntoba, Richard & Clausen, Uwe, 2012. "Dynamic vehicle routing with anticipation in disaster relief," Socio-Economic Planning Sciences, Elsevier, vol. 46(4), pages 261-271.
    4. de la Torre, Luis E. & Dolinskaya, Irina S. & Smilowitz, Karen R., 2012. "Disaster relief routing: Integrating research and practice," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 88-97.
    5. Sheu, Jiuh-Biing & Pan, Cheng, 2014. "A method for designing centralized emergency supply network to respond to large-scale natural disasters," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 284-305.
    6. Dean, Matthew D. & Nair, Suresh K., 2014. "Mass-casualty triage: Distribution of victims to multiple hospitals using the SAVE model," European Journal of Operational Research, Elsevier, vol. 238(1), pages 363-373.
    7. 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.
    8. Caunhye, Aakil M. & Zhang, Yidong & Li, Mingzhe & Nie, Xiaofeng, 2016. "A location-routing model for prepositioning and distributing emergency supplies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 90(C), pages 161-176.
    9. Ahmadi, Morteza & Seifi, Abbas & Tootooni, Behnam, 2015. "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, Elsevier, vol. 75(C), pages 145-163.
    10. Saadatseresht, Mohammad & Mansourian, Ali & Taleai, Mohammad, 2009. "Evacuation planning using multiobjective evolutionary optimization approach," European Journal of Operational Research, Elsevier, vol. 198(1), pages 305-314, October.
    11. Wex, Felix & Schryen, Guido & Feuerriegel, Stefan & Neumann, Dirk, 2014. "Emergency response in natural disaster management: Allocation and scheduling of rescue units," European Journal of Operational Research, Elsevier, vol. 235(3), pages 697-708.
    12. Yi, Wei & Ozdamar, Linet, 2007. "A dynamic logistics coordination model for evacuation and support in disaster response activities," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1177-1193, June.
    13. Rennemo, Sigrid Johansen & Rø, Kristina Fougner & Hvattum, Lars Magnus & Tirado, Gregorio, 2014. "A three-stage stochastic facility routing model for disaster response planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 116-135.
    14. Najafi, Mehdi & Eshghi, Kourosh & Dullaert, Wout, 2013. "A multi-objective robust optimization model for logistics planning in the earthquake response phase," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 217-249.
    15. Moshe Dror & Pierre Trudeau, 1990. "Split delivery routing," Naval Research Logistics (NRL), John Wiley & Sons, vol. 37(3), pages 383-402, June.
    16. Ruiz, Ruben & Stutzle, Thomas, 2007. "A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 2033-2049, March.
    17. Moshref-Javadi, Mohammad & Lee, Seokcheon, 2016. "The Latency Location-Routing Problem," European Journal of Operational Research, Elsevier, vol. 255(2), pages 604-619.
    18. Goerigk, Marc & Deghdak, Kaouthar & Heßler, Philipp, 2014. "A comprehensive evacuation planning model and genetic solution algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 82-97.
    19. Moshe Dror & Pierre Trudeau, 1989. "Savings by Split Delivery Routing," Transportation Science, INFORMS, vol. 23(2), pages 141-145, May.
    20. Berkoune, Djamel & Renaud, Jacques & Rekik, Monia & Ruiz, Angel, 2012. "Transportation in disaster response operations," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 23-32.
    21. Yi, Wei & Kumar, Arun, 2007. "Ant colony optimization for disaster relief operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 660-672, November.
    22. Yugang Yu & Chengbin Chu & Haoxun Chen & Feng Chu, 2012. "Large scale stochastic inventory routing problems with split delivery and service level constraints," Annals of Operations Research, Springer, vol. 197(1), pages 135-158, August.
    23. Cattaruzza, Diego & Absi, Nabil & Feillet, Dominique & Vidal, Thibaut, 2014. "A memetic algorithm for the Multi Trip Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 236(3), pages 833-848.
    24. 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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    Cited by:

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    15. Sachin Modgil & Rohit Kumar Singh & Cyril Foropon, 2022. "Quality management in humanitarian operations and disaster relief management: a review and future research directions," Annals of Operations Research, Springer, vol. 319(1), pages 1045-1098, December.
    16. Fatemeh Faghih-Mohammadi & Mohammad Mahdi Nasiri & Dinçer Konur, 2023. "Cross-dock facility for disaster relief operations," Annals of Operations Research, Springer, vol. 322(1), pages 497-538, March.
    17. Hasti Seraji & Reza Tavakkoli-Moghaddam & Sobhan Asian & Harpreet Kaur, 2022. "An integrative location-allocation model for humanitarian logistics with distributive injustice and dissatisfaction under uncertainty," Annals of Operations Research, Springer, vol. 319(1), pages 211-257, December.

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