An optimization model for evacuating people with disability in extreme disaster conditions: A case study

Abstract

The increasing severity and frequency of disasters have posed major challenges for people. Amongst, the risks of fatalities and injuries of People With Disabilities (PWDs) have signi cantly increased. The Sendai Framework for Disaster Risk Reduction (SFDRR) initiated a movement to create a \disability-accessible and inclusive environment", which highlighted the problems PWDs faced during disasters. One of the most important issues is to provide evacuation and accommodation according to the special needs of PWDs. In this study, a Mixed-Integer Linear Programming (MILP) model is proposed to pick up PWDs from di erent locations and transfer them to shelters. Throughout this research, diverse disabilities, heterogonous vehicles, compatibility types of disabilities and vehicles, multi-depot, and adept and amateur operators are considered to help evacuate PWDs. Also, 27 problems are solved to examine the efficacy of (μ + 1) Evolutionary Algorithm (EA) in the case of large-scale problems. Subsequently, a real case study with 500 nodes (including pick-up, shelter, and depot nodes) is analyzed. The computational results illustrate that by adding small-sized (car) and medium-sized (van) vehicles to the current eet, the time for tours traveled signi cantly is reduced. Finally, a sensitivity analysis is conducted to prepare some managerial implications for crisis managers during the occurrence of disasters to help PWDs during evacuation.