Determining optimal fuel strategies under uncertainty

Dominiqueca Edwards, Lauren Davis, Pitu Mirchandani

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In preparation for a hurricane, individuals affected often are required to evacuate. Evacuations can cause high increases in the demand for gasoline fuel. The purpose of this research is to determine alternate delivery locations and times for fuel vessels scheduled to arrive at a port that is impacted by an approaching hurricane. Motivated by the impact of Hurricane Irma in Florida, we develop a multi-period stochastic scheduling model that incorporates hurricane advisories, scheduled fuel deliveries, maritime port storage capacity and vessel capacity in a maritime port network. Our model determines the best delivery schedule based on multiple objectives. The first minimizes total unmet demand at each port. The second objective captures inequity in unmet demand across the port network. We conduct a numerical study based on fuel delivery data from maritime ports in Florida. The results show we are able to determine alternative delivery schedules for each vessel. One of the key findings is that the port availability is the driving factor in determining the vessel schedules.

Original languageEnglish (US)
Title of host publicationProceedings of the 2020 IISE Annual Conference
EditorsL. Cromarty, R. Shirwaiker, P. Wang
PublisherInstitute of Industrial and Systems Engineers, IISE
Number of pages7
ISBN (Electronic)9781713827818
StatePublished - 2020
Event2020 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2020 - Virtual, Online, United States
Duration: Nov 1 2020Nov 3 2020

Publication series

NameProceedings of the 2020 IISE Annual Conference


Conference2020 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2020
Country/TerritoryUnited States
CityVirtual, Online


  • Fuel Supply Chain
  • Humanitarian Relief
  • Hurricane
  • Port operations

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering


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