A Conflict-Based Path-Generation Heuristic for Evacuation Planning

TL;DR

This paper introduces a conflict-based path-generation heuristic for evacuation planning that efficiently generates routes to optimize large-scale evacuations in real time, significantly reducing computational complexity.

Contribution

It presents a novel conflict-based path-generation heuristic that lazily generates evacuation routes and optimizes them in a master problem, enabling near-real-time solutions for large-scale scenarios.

Findings

Reduces variables from 4.5 million to 30,000 in case study

Enables near-optimal evacuation planning in real time

Successfully applied to flood scenarios with 70,000 evacuees

Abstract

Evacuation planning and scheduling is a critical aspect of disaster management and national security applications. This paper proposes a conflict-based path-generation approach for evacuation planning. Its key idea is to generate evacuation routes lazily for evacuated areas and to optimize the evacuation over these routes in a master problem. Each new path is generated to remedy conflicts in the evacuation and adds new columns and a new row in the master problem. The algorithm is applied to massive flood scenarios in the Hawkesbury-Nepean river (West Sydney, Australia) which require evacuating in the order of 70,000 persons. The proposed approach reduces the number of variables from 4,500,000 in a Mixed Integer Programming (MIP) formulation to 30,000 in the case study. With this approach, realistic evacuations scenarios can be solved near-optimally in real time, supporting both evacuation planning in strategic, tactical, and operational environments.