Sustainability-Oriented Policy–Terrain-Coupled Mixed-Fleet Routing for Scenario-Based Green Urban Freight Logistics

Abstract

Sustainable urban freight logistics requires routing decisions that jointly account for operating cost, vehicle technology, low-emission-zone (LEZ) access, terrain-sensitive energy use, and battery feasibility. This study develops a policy–terrain-coupled mixed-fleet routing framework integrating LEZ exposure, system-level carbon settlement, terrain-sensitive energy consumption, electric-vehicle (EV) battery feasibility, and route-level EV/internal-combustion-engine vehicle reassignment within a unified daily total operational cost (DTOC) evaluator. An adaptive large-neighborhood search (ALNS) procedure reconstructs feasible routes, while vehicle type is re-evaluated through counterfactual comparison of the complete system objective. The main experiments use 60 enhanced Gehring–Homberger benchmark-derived scenarios and 20 independent seeds, supplemented by ablation, carbon-price, EV-fixed-cost, heuristic-weight, convergence, and customer-scale scalability analyses. The ALNS-based framework achieves the lowest mean DTOC among the tested procedures, albeit with higher runtime. Policy and terrain information alter modeled fleet composition, with topology-dependent cost effects. Lower EV fixed costs consistently increase EV share, whereas carbon-price effects vary across network structures. All runs in the additional 200–1000-customer tests were feasible, although runtime increased with problem size. London- and Madrid-informed cases are treated as archetypes rather than as real-world validation cases. These results provide a basis for scenario screening and comparative planning of policy–terrain interactions before city-specific calibration and deployment.