Work

A branch-and-price algorithm for robust truck-drone collaborative routing problem with road restoration uncertainty in disaster relief

Year: 2025

Type: conference-paper

Abstract: With the frequent occurrence of natural disasters and extreme weather, the issue of relief transportation in humanitarian logistics has become increasingly critical. In disaster-affected areas, roads are often blocked by debris, requiring trucks to clear obstacles and restore the accessibility of roads before they can pass. Moreover, the uncertainty of road damage further complicates rescue efforts. Drones, unaffected by road conditions, serve as excellent auxiliary tools for trucks. This study addresses a robust truck-drone collaborative routing problem integrating road restoration and relief delivery. A truck and a drone are deployed to deliver supplies, aiming to maximize the fulfillment of prioritized demands within the limited rescue time. We have constructed a model for this problem and proposed a Branch-and-Price algorithm with customized labeling algorithm for task allocation in road restoration and rescue material delivery. The computational results demonstrate its superior performance, making the method well-suited for route planning in emergency rescue scenarios.

Source: International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC)

DOI: 10.1145/3745533.3745543

Authors: Qianru Li, Xuting Sun

Institution: Shanghai University

Language: English

Topic: Vehicle Routing Optimization Methods

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Funder: National Natural Science Foundation of China