Urban freight demand has increased with e-commerce, intensifying traffic congestion, air pollution, and greenhouse gas emissions. To address these challenges, we propose a delivery model combining microhubs and crowdshipping (M+C). Trucks visit only microhubs, while crowdshippers—individuals making personal trips—handle first and last-mile deliveries. This reduces truck related emissions, noise pollution, and congestion in urban areas. We formulate the truck routing problem as a Many-to-Many Pickup-and-Delivery Problem with Split Loads (M2MPDPSL), which allows heterogeneous commodities and multi-visits to microhubs. We synchronize trucks and crowdshippers by linking parcel availability and time windows across both layers. An enhanced Adaptive Large Neighborhood Search (ALNS) with tailored operators is developed to solve the problem and validated using both standard benchmark instances and customized scenarios. We then compare the M+C system to a traditional Depot-Based (DB) approach and results show that M+C reduces operational cost and truck miles traveled, especially in dense customer settings.
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