An Adaptive Variable Neighborhood Search for a Family of Set Covering Routing Problems with an Application in Disaster Relief Operations
Andreas Hagn, Jan Krause, Moritz Stargalla, Lorenza Moreno

TL;DR
This paper introduces an adaptive variable neighborhood search method for a complex set covering routing problem tailored to disaster relief logistics, integrating helicopter and ground transportation constraints.
Contribution
It develops a novel AVNS algorithm combining routing and covering decisions for a hybrid transportation model in disaster scenarios.
Findings
The AVNS approach achieves competitive solutions on benchmark instances.
Application to a real-world flood case demonstrates practical effectiveness.
The framework offers managerial insights for disaster response logistics.
Abstract
This paper studies a variant of the Set Covering Routing Problem (SCRP) motivated by post-disaster humanitarian logistics. We consider a hybrid distribution concept in which the majority of transportation is performed by helicopters, while ground transport is limited to the last mile, addressing severe accessibility constraints in disaster-affected regions. The resulting problem integrates landing site location, routing, and covering decisions, incorporating features of the Multi-Vehicle Covering Tour Problem (m-CTP) and the Vehicle Routing with Demand Allocation Problem (VRDAP) in a facility-capacitated, multi-depot setting. Due to the computational complexity of the problem, we develop an Adaptive Variable Neighborhood Search (AVNS) that combines established routing operators with novel mechanisms for covering decisions. The performance of the proposed approach is evaluated on…
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