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COVID-19 repatriation programs - Classification and optimization models.

Sameh Al-Shihabi1,2, Mohammed M AlDurgham3,4, Mazen Arafeh2

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This study addresses international repatriation challenges during pandemics, optimizing flight scheduling to prioritize vulnerable citizens. It offers mathematical models for efficient repatriation planning in future crises.

Keywords:
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Area of Science:

  • Operations Research
  • Public Health
  • International Relations

Background:

  • The COVID-19 pandemic necessitated complex repatriation efforts due to border closures and flight suspensions.
  • Traditional airline scheduling differs from repatriation, where demand dictates flight planning.
  • Prioritizing vulnerable populations is a key constraint in repatriation logistics.

Purpose of the Study:

  • To provide an optimization perspective on international repatriation problems.
  • To analyze and compare repatriation strategies, using India and Jordan as case studies.
  • To develop and demonstrate mixed-integer linear programming (MILP) models for repatriation planning.

Main Methods:

  • Comparative analysis of Indian and Jordanian repatriation programs.
  • Development of mixed-integer linear programming (MILP) models for various repatriation phases.
  • Solving illustrative examples and a two-stage problem mirroring Jordan's repatriation program.

Main Results:

  • Identified similarities and differences in national repatriation approaches.
  • Demonstrated the applicability of MILP models for optimizing repatriation logistics.
  • Provided a framework for decision-making in complex repatriation scenarios.

Conclusions:

  • Optimization models can significantly enhance the efficiency and equity of repatriation efforts.
  • The developed MILP models offer a valuable tool for managing future international repatriation crises.
  • This research supports policymakers and researchers in preparing for similar global health emergencies.