Distributionally robust fairness-based last-mile relief network optimization with casualty uncertainty

Key Points

• Optimizing last-mile relief networks leads to improved fairness and efficiency under casualty uncertainty.
• The analysis reveals that integrating robust fairness metrics can enhance outcomes by up to 25%.
• The approach utilizes distributionally robust optimization to address variations in casualty estimates during disasters.
• This framework may enable more equitable resource distribution, highlighting the need for robust models in emergency logistics.