Abstract
Since delivery robots share sidewalks with pedestrians, it may be beneficial to choose paths for them that avoid zones with high pedestrian density. In this paper, we investigate a robot-based last-mile delivery problem considering path flexibility given the presence of zones with varying pedestrian level of service (LOS). Pedestrian LOS is a measure of pedestrian flow density. We model this new problem with stochastic travel times and soft customer time windows. The model includes an objective that reflects customer service quality based on early and late arrivals. The heuristic solution approach uses the minimum travel time paths from different LOS zones (path flexibility). We demonstrate that the presence of pedestrian zones leads to alternative path choices in 30% of all cases. In addition, we find that extended time windows may help increase service quality in zones with high pedestrian density by up to 40%.
Highlights
There are many challenges associated with last-mile delivery, the final step in the retail supply chain
Unlike related work, which mostly focuses on deterministic travel times, we explore the effect of stochastic travel times caused by pedestrian level of service (LOS) zones on robot-based deliveries
We present the average objective function values, the average percentage increase of the objective function compared to the Free-Flow scenario (% obj Δ), the average total distance traveled by all robots, the average total distance traveled in the inner zone (Q Dist) and the outer zone (P Dist) if applicable, the average percentage of distance traveled in the inner (%Q km) and the outer (%P km) zones, the average expected total travel times in hours, the average expected travel time in the inner (Q time) and outer (P time) zones, and the average percentage of expected travel time in the inner (%Q time) and the outer (%P time) zones
Summary
There are many challenges associated with last-mile delivery, the final step in the retail supply chain. It is estimated that the last mile constitutes about half of all logistics costs for service providers (McKinsey and Company, 2016). This is due to the number of failed deliveries, which leads to additional delivery attempts and increased costs. The rapid growth of e-commerce has increased the demand for delivery drivers (Sasso, 2018) and resulted in driver shortages. With the spread of COVID−19, demand for last-mile delivery services has increased even further. Given these factors, many logistics service providers are exploring alternative solutions for last-mile deliveries
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