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The Emergency Vehicle Routing Problem with Uncertain Demand under Sustainability Environments

Author

Listed:
  • Jin Qin

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410012, China)

  • Yong Ye

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410012, China)

  • Bi-rong Cheng

    (School of Information Engineering, Wuyi University, Nanping 354300, China)

  • Xiaobo Zhao

    (Guangzhou Port Company Ltd., Guangzhou 510100, China)

  • Linling Ni

    (Dongfang College, Zhejiang University of Finance & Economics, Hangzhou 310000, China)

Abstract

The reasonable utilization of limited resources is critical to realize the sustainable developments. In the initial 72-h crucial rescue period after the disaster, emergency supplies have always been insufficient and the demands in the affected area have always been uncertain. In order to improve timeliness, utilization and sustainability of emergency service, the allocation of the emergency supplies and the emergency vehicle routes should be determined simultaneously. Assuming the uncertain demands follow normal distribution, an optimization model for the emergency vehicle routing, by considering the insufficient supplies and the uncertain demands, is developed. The objective function is applied to minimize the total costs, including the penalty costs induced by more or less supplies than the actual demands at all demand points, as well as the constraints of the time windows and vehicle load capacity taken into account. In more details, a solution method for the model, based on the genetic algorithm, is proposed, which solves the problem in two stages. A numerical example is presented to demonstrate the efficiency and validity of the proposed model and algorithm.

Suggested Citation

  • Jin Qin & Yong Ye & Bi-rong Cheng & Xiaobo Zhao & Linling Ni, 2017. "The Emergency Vehicle Routing Problem with Uncertain Demand under Sustainability Environments," Sustainability, MDPI, vol. 9(2), pages 1-24, February.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:2:p:288-:d:90924
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    References listed on IDEAS

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    1. Lai, David S.W. & Caliskan Demirag, Ozgun & Leung, Janny M.Y., 2016. "A tabu search heuristic for the heterogeneous vehicle routing problem on a multigraph," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 86(C), pages 32-52.
    2. Meryem Berghida & Abdelmadjid Boukra, 2015. "Resolution of a Vehicle Routing Problem with Simultaneous Pickup and Delivery: A Cooperative Approach," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 6(3), pages 53-68, July.
    3. Novoa, Clara & Storer, Robert, 2009. "An approximate dynamic programming approach for the vehicle routing problem with stochastic demands," European Journal of Operational Research, Elsevier, vol. 196(2), pages 509-515, July.
    4. Anna Nagurney & Amir Masoumi & Min Yu, 2012. "Supply chain network operations management of a blood banking system with cost and risk minimization," Computational Management Science, Springer, vol. 9(2), pages 205-231, May.
    5. Anna Nagurney & Min Yu & Qiang Qiang, 2011. "Supply chain network design for critical needs with outsourcing," Papers in Regional Science, Wiley Blackwell, vol. 90(1), pages 123-142, March.
    6. Allahyari, Somayeh & Salari, Majid & Vigo, Daniele, 2015. "A hybrid metaheuristic algorithm for the multi-depot covering tour vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 242(3), pages 756-768.
    7. Sheu, Jiuh-Biing, 2007. "An emergency logistics distribution approach for quick response to urgent relief demand in disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 687-709, November.
    8. Sheu, Jiuh-Biing, 2007. "Challenges of emergency logistics management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 655-659, November.
    9. Hochbaum, Dorit S. & Shmoys, David B., 1986. "Best possible heuristics for the bottleneck wandering salesperson and bottleneck vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 26(3), pages 380-384, September.
    10. Sheu, Jiuh-Biing, 2010. "Dynamic relief-demand management for emergency logistics operations under large-scale disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(1), pages 1-17, January.
    11. Dong, June & Zhang, Ding & Nagurney, Anna, 2004. "A supply chain network equilibrium model with random demands," European Journal of Operational Research, Elsevier, vol. 156(1), pages 194-212, July.
    12. Caunhye, Aakil M. & Nie, Xiaofeng & Pokharel, Shaligram, 2012. "Optimization models in emergency logistics: A literature review," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 4-13.
    13. Zhang, Junlong & Lam, William H.K. & Chen, Bi Yu, 2016. "On-time delivery probabilistic models for the vehicle routing problem with stochastic demands and time windows," European Journal of Operational Research, Elsevier, vol. 249(1), pages 144-154.
    14. Jalel Euchi & Habib Chabchoub & Adnan Yassine, 2011. "New Evolutionary Algorithm Based on 2-Opt Local Search to Solve the Vehicle Routing Problem with Private Fleet and Common Carrier," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 2(1), pages 58-82, January.
    15. Errico, F. & Desaulniers, G. & Gendreau, M. & Rei, W. & Rousseau, L.-M., 2016. "A priori optimization with recourse for the vehicle routing problem with hard time windows and stochastic service times," European Journal of Operational Research, Elsevier, vol. 249(1), pages 55-66.
    16. Wang, Haijun & Du, Lijing & Ma, Shihua, 2014. "Multi-objective open location-routing model with split delivery for optimized relief distribution in post-earthquake," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 160-179.
    17. Pillac, Victor & Gendreau, Michel & Guéret, Christelle & Medaglia, Andrés L., 2013. "A review of dynamic vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 225(1), pages 1-11.
    18. 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.
    19. J Berger & M Barkaoui, 2003. "A new hybrid genetic algorithm for the capacitated vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(12), pages 1254-1262, December.
    20. Gladys Maquera & Manuel Laguna & Dan Abensur Gandelman & Annibal Parracho Sant’Anna, 2011. "Scatter Search Applied to the Vehicle Routing Problem with Simultaneous Delivery and Pickup," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 2(2), pages 1-20, April.
    21. Lin, Yen-Hung & Batta, Rajan & Rogerson, Peter A. & Blatt, Alan & Flanigan, Marie, 2011. "A logistics model for emergency supply of critical items in the aftermath of a disaster," Socio-Economic Planning Sciences, Elsevier, vol. 45(4), pages 132-145, December.
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    Cited by:

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    2. Jesica de Armas & Jessica Rodríguez-Pereira & Bruno Vieira & Helena Ramalhinho, 2021. "Optimizing Assistive Technology Operations for Aging Populations," Sustainability, MDPI, vol. 13(12), pages 1-27, June.
    3. Junhu Ruan & Felix T. S. Chan & Xiaofeng Zhao, 2018. "Re-Planning the Intermodal Transportation of Emergency Medical Supplies with Updated Transfer Centers," Sustainability, MDPI, vol. 10(8), pages 1-20, August.
    4. Cunrui Ma & Baohua Mao & Qi Xu & Guodong Hua & Sijia Zhang & Tong Zhang, 2018. "Multi-Depot Vehicle Routing Optimization Considering Energy Consumption for Hazardous Materials Transportation," Sustainability, MDPI, vol. 10(10), pages 1-21, September.
    5. Rafidah Md Noor & Nadia Bella Gustiani Rasyidi & Tarak Nandy & Raenu Kolandaisamy, 2020. "Campus Shuttle Bus Route Optimization Using Machine Learning Predictive Analysis: A Case Study," Sustainability, MDPI, vol. 13(1), pages 1-24, December.
    6. Di Wu & Xuejun Ji & Fang Xiao & Shijie Sheng, 2022. "A Location Inventory Routing Optimisation Model and Algorithm for a Remote Island Shipping Network considering Emergency Inventory," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    7. Cong Wang & Zhongxiu Peng & Wenqing Xu, 2023. "Robust Bi-Level Optimization for Maritime Emergency Materials Distribution in Uncertain Decision-Making Environments," Mathematics, MDPI, vol. 11(19), pages 1-30, September.
    8. Yanyan Wang & Baiqing Sun, 2022. "Multiperiod optimal emergency material allocation considering road network damage and risk under uncertain conditions," Operational Research, Springer, vol. 22(3), pages 2173-2208, July.
    9. Joaquín Pacheco & Manuel Laguna, 2020. "Vehicle routing for the urgent delivery of face shields during the COVID-19 pandemic," Journal of Heuristics, Springer, vol. 26(5), pages 619-635, October.

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