IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i19p3624-d932930.html
   My bibliography  Save this article

Multitask Emergency Logistics Planning under Multimodal Transportation

Author

Listed:
  • Hongbin Liu

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China)

  • Guopeng Song

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China)

  • Tianyu Liu

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China)

  • Bo Guo

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China)

Abstract

Multitask emergency logistics planning is a complex optimization problem in practice. When a disaster occurs, relief materials or rescue teams should be dispatched to destinations as soon as possible. In a nutshell, the problem can be described as an optimization of multipoint-to-multipoint transportation delivery problem in a given multimodal traffic network. In this study, a multimodal traffic network is considered for emergency logistics transportation planning, and a mixed-integer programming (MIP) formulation is proposed to model the problem. In order to solve this model, we propose a two-layer solution method. The inner layer is to manage the single-task route recommendation, for which we develop a shortest-path algorithm with the multimodal traffic network. Here, the optimal substructure of the algorithm and its time complexity are presented. With the route of each task calculated by the single-task solver, a general optimization algorithm based on improved particle swarm optimization (PSO) is proposed at the outer layer to coordinate the execution of each task constrained by the limited transportation capacity, so as to derive solutions for multi-commodity emergency logistics planning. Extensive computational results show that the proposed method can find solutions of good quality in reasonable time. Meanwhile, through the sensitivity analysis of the algorithm, we find the appropriate parameters for general optimization algorithm to solve the problem proposed in this paper. The proposed approach is effective and practical for solving multitask emergency logistics planning problem under multimodal transportation, which can find a satisfactory solution in an acceptable time.

Suggested Citation

  • Hongbin Liu & Guopeng Song & Tianyu Liu & Bo Guo, 2022. "Multitask Emergency Logistics Planning under Multimodal Transportation," Mathematics, MDPI, vol. 10(19), pages 1-25, October.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:19:p:3624-:d:932930
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/19/3624/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/10/19/3624/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kai Lei & Xiaoning Zhu & Jianfei Hou & Wencheng Huang, 2014. "Decision of Multimodal Transportation Scheme Based on Swarm Intelligence," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-10, April.
    2. Kasin Ransikarbum & Scott J. Mason, 2016. "Multiple-objective analysis of integrated relief supply and network restoration in humanitarian logistics operations," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 49-68, January.
    3. Barbarosoglu, Gulay & Ozdamar, Linet & Cevik, Ahmet, 2002. "An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations," European Journal of Operational Research, Elsevier, vol. 140(1), pages 118-133, July.
    4. Subramanian, Anand & Penna, Puca Huachi Vaz & Uchoa, Eduardo & Ochi, Luiz Satoru, 2012. "A hybrid algorithm for the Heterogeneous Fleet Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 221(2), pages 285-295.
    5. Mohammadi, Mehrdad & Jula, Payman & Tavakkoli-Moghaddam, Reza, 2017. "Design of a reliable multi-modal multi-commodity model for hazardous materials transportation under uncertainty," European Journal of Operational Research, Elsevier, vol. 257(3), pages 792-809.
    6. 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.
    7. Zhou, Yaoming & Kundu, Tanmoy & Qin, Wei & Goh, Mark & Sheu, Jiuh-Biing, 2021. "Vulnerability of the worldwide air transportation network to global catastrophes such as COVID-19," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    8. Özdamar, Linet & Ertem, Mustafa Alp, 2015. "Models, solutions and enabling technologies in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 244(1), pages 55-65.
    9. Cynthia Barnhart & Yosef Sheffi, 1993. "A Network-Based Primal-Dual Heuristic for the Solution of Multicommodity Network Flow Problems," Transportation Science, INFORMS, vol. 27(2), pages 102-117, May.
    10. Yoon, Soovin & Albert, Laura A., 2021. "Dynamic dispatch policies for emergency response with multiple types of vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    11. G Barbarosoǧlu & Y Arda, 2004. "A two-stage stochastic programming framework for transportation planning in disaster response," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(1), pages 43-53, January.
    12. 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.
    13. Cynthia Barnhart, 1993. "Dual‐ascent methods for large‐scale multicommodity flow problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 40(3), pages 305-324, April.
    14. 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.
    15. Haghani, Ali & Oh, Sei-Chang, 1996. "Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 30(3), pages 231-250, May.
    16. Wapee Manopiniwes & Takashi Irohara, 2017. "Stochastic optimisation model for integrated decisions on relief supply chains: preparedness for disaster response," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 979-996, February.
    17. Alem, Douglas & Clark, Alistair & Moreno, Alfredo, 2016. "Stochastic network models for logistics planning in disaster relief," European Journal of Operational Research, Elsevier, vol. 255(1), pages 187-206.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yanbin Chang & Yongjia Song & Burak Eksioglu, 2022. "A stochastic look-ahead approach for hurricane relief logistics operations planning under uncertainty," Annals of Operations Research, Springer, vol. 319(1), pages 1231-1263, December.
    2. Rodolfo Modrigais Strauss Nunes & Susana Carla Farias Pereira, 2022. "Intellectual structure and trends in the humanitarian operations field," Annals of Operations Research, Springer, vol. 319(1), pages 1099-1157, December.
    3. A. Anaya-Arenas & J. Renaud & A. Ruiz, 2014. "Relief distribution networks: a systematic review," Annals of Operations Research, Springer, vol. 223(1), pages 53-79, December.
    4. Abhishek Behl & Pankaj Dutta, 2019. "Humanitarian supply chain management: a thematic literature review and future directions of research," Annals of Operations Research, Springer, vol. 283(1), pages 1001-1044, December.
    5. Doan, Xuan Vinh & Shaw, Duncan, 2019. "Resource allocation when planning for simultaneous disasters," European Journal of Operational Research, Elsevier, vol. 274(2), pages 687-709.
    6. Özdamar, Linet & Ertem, Mustafa Alp, 2015. "Models, solutions and enabling technologies in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 244(1), pages 55-65.
    7. Yiping Jiang & Yufei Yuan, 2019. "Emergency Logistics in a Large-Scale Disaster Context: Achievements and Challenges," IJERPH, MDPI, vol. 16(5), pages 1-23, March.
    8. Wilson, Duncan T. & Hawe, Glenn I. & Coates, Graham & Crouch, Roger S., 2013. "A multi-objective combinatorial model of casualty processing in major incident response," European Journal of Operational Research, Elsevier, vol. 230(3), pages 643-655.
    9. Sheu, Jiuh-Biing, 2014. "Post-disaster relief–service centralized logistics distribution with survivor resilience maximization," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 288-314.
    10. Zhongzhen Yang & Liquan Guo & Zaili Yang, 2019. "Emergency logistics for wildfire suppression based on forecasted disaster evolution," Annals of Operations Research, Springer, vol. 283(1), pages 917-937, December.
    11. Rodríguez-Espíndola, Oscar & Ahmadi, Hossein & Gastélum-Chavira, Diego & Ahumada-Valenzuela, Omar & Chowdhury, Soumyadeb & Dey, Prasanta Kumar & Albores, Pavel, 2023. "Humanitarian logistics optimization models: An investigation of decision-maker involvement and directions to promote implementation," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    12. Liu, Kanglin & Yang, Liu & Zhao, Yejia & Zhang, Zhi-Hai, 2023. "Multi-period stochastic programming for relief delivery considering evolving transportation network and temporary facility relocation/closure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
    13. Lei Lei & Michael Pinedo & Lian Qi & Shengbin Wang & Jian Yang, 2015. "Personnel scheduling and supplies provisioning in emergency relief operations," Annals of Operations Research, Springer, vol. 235(1), pages 487-515, December.
    14. 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.
    15. 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.
    16. Junhu Ruan & Xuping Wang & Yan Shi, 2014. "A Two-Stage Approach for Medical Supplies Intermodal Transportation in Large-Scale Disaster Responses," IJERPH, MDPI, vol. 11(11), pages 1-29, October.
    17. Seyed Reza Abazari & Fariborz Jolai & Amir Aghsami, 2022. "Designing a humanitarian relief network considering governmental and non-governmental operations under uncertainty," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(3), pages 1430-1452, June.
    18. Kundu, Tanmoy & Sheu, Jiuh-Biing & Kuo, Hsin-Tsz, 2022. "Emergency logistics management—Review and propositions for future research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    19. Renata Turkeš & Daniel Palhazi Cuervo & Kenneth Sörensen, 2019. "Pre-positioning of emergency supplies: does putting a price on human life help to save lives?," Annals of Operations Research, Springer, vol. 283(1), pages 865-895, December.
    20. Repoussis, Panagiotis P. & Paraskevopoulos, Dimitris C. & Vazacopoulos, Alkiviadis & Hupert, Nathaniel, 2016. "Optimizing emergency preparedness and resource utilization in mass-casualty incidents," European Journal of Operational Research, Elsevier, vol. 255(2), pages 531-544.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:10:y:2022:i:19:p:3624-:d:932930. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.