Year: 2026
Type: article
Abstract: Indonesia is vulnerable to natural disasters, which frequently disrupt ground transportation infrastructure and hinder humanitarian aid distribution. In such conditions, drone-based logistics offers a promising alternative for last-mile delivery to affected areas. This study proposes an integrated optimization framework for humanitarian drone logistics that combines a multi-objective Facility Location Problem (FLP) and a Vehicle Routing Problem (VRP). The FLP determines the optimal locations of drone stations to maximize service coverage while minimizing infrastructure and operational costs, and is formulated as a min-max weighted-sum objective with normalized components. The VRP, solved using a Simulated Annealing (SA) algorithm, optimizes pickup-and-delivery routes with multi-trip capability, subject to drone capacity, distance, and operational time constraints. The framework is evaluated using real disaster data from the 2022 Cianjur earthquake in Indonesia. Results show that a small number of strategically located drone stations achieve high service coverage at a reasonable daily cost, with weight coverage approaching completeness. Routing optimization substantially reduces the deployed fleet relative to the FLP upper bound, demonstrating the added value of the VRP stage as a cost-reduction mechanism. The findings demonstrate that integrated strategic and operational optimization significantly enhances the efficiency and feasibility of drone-based humanitarian logistics, and that objective weight tuning can serve as a practical policy lever for balancing coverage, cost, and equity in disaster relief operations.
DOI: 10.31387/oscm0670551
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
Funder: Universitas Katolik Parahyangan
OpenAlex ID: W7223983419