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Pareto-based grouping meta-heuristic algorithm for humanitarian relief logistics with multistate network reliability

Author

Listed:
  • Maliheh Khorsi

    (Tarbiat Modares University)

  • Seyed Kamal Chaharsooghi

    (Tarbiat Modares University)

  • Ali Husseinzadeh Kashan

    (Tarbiat Modares University)

  • Ali Bozorgi-Amiri

    (University of Tehran)

Abstract

This article considers a biobjective location-routing problem to deliver relief resources to the victims affected by a disaster under uncertainty in demand, transportation infrastructure, and travel time. Since transportation networks are exposed to a considerable level of uncertainty, choosing the reliable path for relief goods to be transmitted to the affected areas ensures the arrival of these supplies. For the first time, route reliability is calculated based on the multistate theory, and the universal generating function technique is used for network reliability assessment. The problem is formulated as a multiperiod robust biobjective mixed-integer programming model. Two objective functions are considered: (a) decreasing the sum of arrival times of relief vehicles at the demand nodes for delivering aids to the affected areas, and (b) increasing the minimum route reliability for all the serving vehicles. A novel multiobjective grouping algorithm is proposed to obtain the Pareto-optimal solutions of the problem. Then, its performance is compared with two other multiobjective grouping algorithms. To evaluate the solution method, the algorithms are implemented on various test problems and compared statistically. A case study is presented to illustrate the potential applicability of our model. Additionally, to determine the effect of the changes in the main parameters of the problem on the value of objective functions, the sensitivity analyses are performed and the managerial insights are given.

Suggested Citation

  • Maliheh Khorsi & Seyed Kamal Chaharsooghi & Ali Husseinzadeh Kashan & Ali Bozorgi-Amiri, 2021. "Pareto-based grouping meta-heuristic algorithm for humanitarian relief logistics with multistate network reliability," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(2), pages 327-365, June.
    • Handle: RePEc:spr:orspec:v:43:y:2021:i:2:d:10.1007_s00291-021-00630-3
    DOI: 10.1007/s00291-021-00630-3
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    1. Yu, Chian-Son & Li, Han-Lin, 2000. "A robust optimization model for stochastic logistic problems," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 385-397, March.
    2. Mete, Huseyin Onur & Zabinsky, Zelda B., 2010. "Stochastic optimization of medical supply location and distribution in disaster management," International Journal of Production Economics, Elsevier, vol. 126(1), pages 76-84, July.
    3. Ann Melissa Campbell & Dieter Vandenbussche & William Hermann, 2008. "Routing for Relief Efforts," Transportation Science, INFORMS, vol. 42(2), pages 127-145, May.
    4. Mina Husseinzadeh Kashan & Ali Husseinzadeh Kashan & Nasim Nahavandi, 2013. "A novel differential evolution algorithm for binary optimization," Computational Optimization and Applications, Springer, vol. 55(2), pages 481-513, June.
    5. 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.
    6. Gregory Levitin, 2005. "The Universal Generating Function in Reliability Analysis and Optimization," Springer Series in Reliability Engineering, Springer, number 978-1-84628-245-4, July.
    7. 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.
    8. Zhong, Shaopeng & Cheng, Rong & Jiang, Yu & Wang, Zhong & Larsen, Allan & Nielsen, Otto Anker, 2020. "Risk-averse optimization of disaster relief facility location and vehicle routing under stochastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    9. 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.
    10. 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.
    11. Zhang, Bo & Li, Hui & Li, Shengguo & Peng, Jin, 2018. "Sustainable multi-depot emergency facilities location-routing problem with uncertain information," Applied Mathematics and Computation, Elsevier, vol. 333(C), pages 506-520.
    12. 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.
    13. 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.
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    Cited by:

    1. Maliheh Khorsi & Seyed Kamal Chaharsooghi & Ali Husseinzadeh Kashan & Ali Bozorgi-Amiri, 2022. "Solving the humanitarian multi-trip cumulative capacitated routing problem via a grouping metaheuristic algorithm," Annals of Operations Research, Springer, vol. 319(1), pages 173-210, December.

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