Datasets and Scripts for Reproducing Results in“UAV-Guided Bi-level Robust Optimization for Multi-hazard Emergency Response: An Exact-Matheuristic Collaborative Approach in Contin-uous-Discrete Nested Spaces”

作者：Jun Luo · 发表于：Mendeley Data · 年份：2026 · DOI：10.17632/xx8ghb4bwv.1 · 研究领域：Computer science、Data mining、Distributed computing

The dataset combines real-world topological network data with simulated mul-ti-hazard emergency scenarios (earthquakes, forest fires, and urban waterlogging). It provides the foundational spatial and computational data required for modeling du-al-layer emergency response systems, which encompass ground rescue routing and unmanned aerial vehicle (UAV) auxiliary reconnaissance path planning. The geographic environments and disaster simulations are designed to evaluate facility site-selection, resource allocation, and routing efficiency under varying levels of hazard intensity. The foundational geospatial and road network data are extracted via OpenStreetMap (OSM) to construct the abstract and concrete sub-systems for the routing models. The dataset incorporates unified structural formulas with disaster-specific coefficients to represent economic costs across different hazard scenarios without requiring disparate cost equations. The dataset includes: • Geospatial and Network Data (city.oms,forest.oms,N30E104.hgt): Geographic coordinates of demand nodes, candidate facility sites, and edge topologies extracted from OSM. These files define the physical constraints and connectivity for both ground vehicles and UAV reconnaissance paths. • Multi-Hazard Scenario Parameters (Disaster_Environment): Simulation data arrays representing earthquake, forest fire, and urban wa-terlogging events. This includes demand distribution, varying intensity levels, and the unified structural cost coeffi...