IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v88y2023ics003801212300112x.html
   My bibliography  Save this article

Determining optimal fuel delivery strategies under uncertainty

Author

Listed:
  • Edwards, Dominiqueca R.
  • Idoko, Faith O.
  • Vogiatzis, Chrysafis
  • Davis, Lauren B.
  • Mirchandani, Pitu

Abstract

During the preparation before a hurricane makes landfall, affected individuals may be asked to evacuate. Large and small-scale evacuations can cause rapid increases in the demand for gasoline fuel. However, during a hurricane vessels carrying gas may be delayed and/or rerouted, adding to the difficulty of providing the necessary gas in affected areas. In this work, we determine alternate delivery locations and times for vessels carrying fuel that are scheduled to arrive and deliver fuel at ports impacted by an approaching hurricane. Motivated by Hurricane Irma in Florida, we develop a multi-period stochastic scheduling model that incorporates hurricane (weather) advisories, fuel delivery schedules, port storage capacities, and port docking capacities. Our model determines the best schedule based on two objectives: (1) minimize the total unmet demand at each port, and (2) minimize inequities in unmet demands among the ports. We also present a case study and a numerical experiment based on fuel delivery data from ports in Florida. Among our key findings is that port availability is the driving factor in determining feasible schedules for vessel gas deliveries. We also present a scheduling heuristic that dynamically adapts to weather advisories so as to minimize the impact of unmet demand in the affected areas.

Suggested Citation

  • Edwards, Dominiqueca R. & Idoko, Faith O. & Vogiatzis, Chrysafis & Davis, Lauren B. & Mirchandani, Pitu, 2023. "Determining optimal fuel delivery strategies under uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
  • Handle: RePEc:eee:soceps:v:88:y:2023:i:c:s003801212300112x
    DOI: 10.1016/j.seps.2023.101612
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S003801212300112X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.seps.2023.101612?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Leonard Heilig & Stefan Voß, 2017. "Information systems in seaports: a categorization and overview," Information Technology and Management, Springer, vol. 18(3), pages 179-201, September.
    2. Abhinav Khare & Qing He & Rajan Batta, 2020. "Predicting gasoline shortage during disasters using social media," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(3), pages 693-726, September.
    3. Li, Xiaoping & Batta, Rajan & Kwon, Changhyun, 2017. "Effective and equitable supply of gasoline to impacted areas in the aftermath of a natural disaster," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 25-34.
    4. Daniel Müller & Kevin Tierney, 2017. "Decision support and data visualization for liner shipping fleet repositioning," Information Technology and Management, Springer, vol. 18(3), pages 203-221, September.
    5. Marsh, Michael T. & Schilling, David A., 1994. "Equity measurement in facility location analysis: A review and framework," European Journal of Operational Research, Elsevier, vol. 74(1), pages 1-17, April.
    6. Swamy, Rahul & Kang, Jee Eun & Batta, Rajan & Chung, Younshik, 2017. "Hurricane evacuation planning using public transportation," Socio-Economic Planning Sciences, Elsevier, vol. 59(C), pages 43-55.
    7. 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.
    8. Nikolaos P. Rachaniotis & Marisa Masvoula, 2020. "A decision tool for scheduling fleets of fuel supply vessels," Operational Research, Springer, vol. 20(3), pages 1543-1557, September.
    9. 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.
    10. Galindo, Gina & Batta, Rajan, 2013. "Prepositioning of supplies in preparation for a hurricane under potential destruction of prepositioned supplies," Socio-Economic Planning Sciences, Elsevier, vol. 47(1), pages 20-37.
    11. Rawls, Carmen G. & Turnquist, Mark A., 2010. "Pre-positioning of emergency supplies for disaster response," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 521-534, May.
    12. Monir Sabbaghtorkan & Rajan Batta & Qing He, 2022. "On the analysis of an idealized model to manage gasoline supplies in a short-notice hurricane evacuation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(3), pages 911-945, September.
    13. Moros-Daza, Adriana & Amaya-Mier, René & Paternina-Arboleda, Carlos, 2020. "Port Community Systems: A structured literature review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 27-46.
    14. Yagci Sokat, Kezban & Zhou, Rui & Dolinskaya, Irina S. & Smilowitz, Karen & Chan, Jennifer, 2016. "Capturing Real-Time Data in Disaster Response Logistics," Journal of Operations and Supply Chain Management (JOSCM), Fundação Getulio Vargas, Escola de Administração de Empresas de São Paulo (FGV EAESP), vol. 9(1), July.
    15. Huang, Michael & Smilowitz, Karen & Balcik, Burcu, 2012. "Models for relief routing: Equity, efficiency and efficacy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 2-18.
    16. Liu, Kanglin & Zhang, Hengliang & Zhang, Zhi-Hai, 2021. "The efficiency, equity and effectiveness of location strategies in humanitarian logistics: A robust chance-constrained approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    17. Eghbal Akhlaghi, Vahid & Campbell, Ann Melissa & de Matta, Renato E., 2021. "Fuel distribution planning for disasters: Models and case study for Puerto Rico," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    18. Gina Galindo Pacheco & Rajan Batta, 2016. "Forecast-driven model for prepositioning supplies in preparation for a foreseen hurricane," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(1), pages 98-113, January.
    19. Avella, Pasquale & Boccia, Maurizio & Sforza, Antonio, 2004. "Solving a fuel delivery problem by heuristic and exact approaches," European Journal of Operational Research, Elsevier, vol. 152(1), pages 170-179, January.
    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. Eghbal Akhlaghi, Vahid & Campbell, Ann Melissa & de Matta, Renato E., 2021. "Fuel distribution planning for disasters: Models and case study for Puerto Rico," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    2. Li, Xiaoping & Batta, Rajan & Kwon, Changhyun, 2017. "Effective and equitable supply of gasoline to impacted areas in the aftermath of a natural disaster," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 25-34.
    3. 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).
    4. Battarra, Maria & Balcik, Burcu & Xu, Huifu, 2018. "Disaster preparedness using risk-assessment methods from earthquake engineering," European Journal of Operational Research, Elsevier, vol. 269(2), pages 423-435.
    5. 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).
    6. Gutjahr, Walter J. & Nolz, Pamela C., 2016. "Multicriteria optimization in humanitarian aid," European Journal of Operational Research, Elsevier, vol. 252(2), pages 351-366.
    7. 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.
    8. Nilay Noyan & Gökçe Kahvecioğlu, 2018. "Stochastic last mile relief network design with resource reallocation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 187-231, January.
    9. Wang, Qingyi & Liu, Zhuomeng & Jiang, Peng & Luo, Li, 2022. "A stochastic programming model for emergency supplies pre-positioning, transshipment and procurement in a regional healthcare coalition," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    10. 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.
    11. Sabbaghtorkan, Monir & Batta, Rajan & He, Qing, 2020. "Prepositioning of assets and supplies in disaster operations management: Review and research gap identification," European Journal of Operational Research, Elsevier, vol. 284(1), pages 1-19.
    12. Gralla, Erica & Goentzel, Jarrod, 2018. "Humanitarian transportation planning: Evaluation of practice-based heuristics and recommendations for improvement," European Journal of Operational Research, Elsevier, vol. 269(2), pages 436-450.
    13. Rezaei-Malek, Mohammad & Tavakkoli-Moghaddam, Reza & Cheikhrouhou, Naoufel & Taheri-Moghaddam, Alireza, 2016. "An approximation approach to a trade-off among efficiency, efficacy, and balance for relief pre-positioning in disaster management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 485-509.
    14. 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.
    15. 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.
    16. Peiyu Zhang & Yankui Liu & Guoqing Yang & Guoqing Zhang, 2022. "A multi-objective distributionally robust model for sustainable last mile relief network design problem," Annals of Operations Research, Springer, vol. 309(2), pages 689-730, February.
    17. Ali Ekici & Okan Örsan Özener, 2020. "Inventory routing for the last mile delivery of humanitarian relief supplies," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(3), pages 621-660, September.
    18. Li Zhu & Yeming Gong & Yishui Xu & Jun Gu, 2019. "Emergency relief routing models for injured victims considering equity and priority," Annals of Operations Research, Springer, vol. 283(1), pages 1573-1606, December.
    19. Shiripour, Saber & Mahdavi-Amiri, Nezam, 2019. "Optimal distribution of the injured in a multi-type transportation network with damage-dependent travel times: Two metaheuristic approaches," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    20. Wang, Qingyi & Nie, Xiaofeng, 2022. "A stochastic programming model for emergency supply planning considering transportation network mitigation and traffic congestion," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).

    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:eee:soceps:v:88:y:2023:i:c:s003801212300112x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/seps .

    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.