*Result*: An innovative framework integrating MILP and a parallel optimal algorithm for UAV-Enabled last-Mile delivery.

Title:
An innovative framework integrating MILP and a parallel optimal algorithm for UAV-Enabled last-Mile delivery.
Authors:
Amirteimoori, Arash1 (AUTHOR) amirteia@mcmaster.ca, Kia, Reza2 (AUTHOR), Mohamed, Moataz3 (AUTHOR), Weber, Gerhard-Wilhelm4 (AUTHOR)
Source:
International Journal of Production Research. Feb2026, Vol. 64 Issue 3, p777-797. 21p.
Database:
Business Source Premier

*Further Information*

*Urban last-mile delivery faces scalability, cost, and environmental challenges due to truck-based systems' congestion and emissions. This study proposes a Customer-Centric UAV Last-Mile Delivery (CULMD) framework, eliminating truck dependency by optimising UAV routing, charging infrastructure, and sequencing for sustainable urban logistics. We introduce the Parallel Optimal Algorithm with MILP (POAM), a novel approach that decomposes the problem into two sub-problems: parallelised exact combinatorial optimisation for tour and parcel allocation, and MILP-based routing. POAM leverages multi-core CPU parallelisation to solve tour allocation across multiple regions and delivery windows concurrently, ensuring global optimality while reducing runtime by 21.5% compared to the Two-Stage Model (TSM) and 16-fold compared to the Integrated Model (IM). It outperforms metaheuristics like the Artificial Lemming Algorithm (ALA) and Hybrid Genetic Algorithm with Type-Aware Chromosomes (HGATAC+) by 12% and 11% in objective value, respectively. Sensitivity analyses show a 20% increase in regions cuts runtime by 68%, and a 20% increase in UAV load capacity reduces it by 22%. The CULMD framework, powered by POAM, advances sustainable logistics by minimising costs and environmental impacts, offering scalable solutions for urban delivery systems. [ABSTRACT FROM AUTHOR]

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