Yedilkhan D., Shalakhmetov A., Mendaliyev B., Khaimuldin N.
Strategic Capacity Planning Algorithm for Last-Mile Delivery Under High-Volume Demand Surges // Algorithms. — 2026. — Vol. 19, No. 4. — Article No. 319. — DOI: 10.3390/a19040319.

Abstract: Last-mile delivery systems can face extreme demand surges where large volumes of orders exceed courier capacity. In such scenarios, fast and feasibility-first planning becomes more practical than optimal route construction. This paper proposes a hierarchical decomposition pipeline designed to generate shift-feasible clusters under strict shift-duration constraints using travel-time-based estimates. Unlike classical vehicle routing approaches that focus on route quality or demand balancing, the proposed method targets rapid capacity planning for extreme demand events, aiming to estimate an upper bound on courier shifts within seconds. The framework combines topology-preserving spatial linearization using a Hilbert Space-Filling Curve, adaptive greedy microclustering based on travel-time quantiles, and lexicographic dynamic programming to minimize the number of shifts and total travel time. Experimental results show that the proposed approach is significantly faster—up to 187 to 1315 times—than monolithic optimization baselines, demonstrating its suitability for real-time strategic logistics planning under high-demand conditions.

Link / DOI: https://doi.org/10.3390/a19040319