arXiv subjects

Paul Schonfeld

Publications and source records attributed to Paul Schonfeld.

4 recordsLinked to original sources

arXiv2026

Energy-Efficient Drone Logistics for Last-Mile Delivery: Implications of Payload-Dependent Routing Strategies

Drone delivery is rapidly emerging as a cost-effective and energy efficient alternative for last-mile delivery. Unlike ground vehicles, a drone's energy consumption depends on its payload in addition to travel distance. This creates a unique environmental challenge for multi-stop delivery tours, as the drone's total weight, and therefore its energy consumption rate, dynamically changes after each delivery. This paper investigates a novel green drone routing problem focused on maximizing energy efficiency. Through a series of motivating examples and numerical experiments, we demonstrate that energy-aware routing leads to several counter-intuitive routing strategies that contradict traditional distance-minimization delivery: a longer route may actually consume less energy than a shorter one; separate single-customer tours can be superior to a multi-stop tour; and a heterogeneous fleet, with drones of varying sizes, can achieve greater efficiency by matching drone capacity to specific delivery demands. In the numerical study, the green routing strategy shows energy savings in 67% of the instances. For these cases, the average energy saving is 2.17%, with a maximum saving of 5.97%, compared to minimum distance routing. These findings highlight the potential for green drone routing strategies to improve the sustainability of last-mile delivery.

cs.ET↗

arXiv2025

Equity-aware Design and Timing of Fare-free Transit Zoning under Demand Uncertainty

We propose the first analytical stochastic model for optimizing the configuration and implementation policies of fare-free transit. The model focuses on a transportation corridor with two transportation modes: automobiles and buses. The corridor is divided into two sections, an inner one with fare-free transit service and an outer one with fare-based transit service. Under the static version of the model, the optimized length and frequency of the fare-free transit zone can be determined by maximizing total social welfare. The findings indicate that implementing fare-free transit can increase transit ridership and reduce automobile use within the fare-free zone while social equity among the demand groups can be enhanced by lengthening the fare-free zone. Notably, the optimal zone length increases when both social welfare and equity are considered jointly, compared to only prioritizing social welfare. The dynamic model, framed within a market entry and exit real options approach, solves the fare policy switching problem, establishing optimal timing policies for activating or terminating fare-free service. The results from dynamic models reveal earlier implementation and extended durations of fare-free transit in the social welfare-aware regime, driven by lower thresholds compared to the social equity-aware regime.

math.OC↗

arXiv2025

Optimized dynamic scheduling of an exclusive bus lane or high occupancy vehicle lane in a bimodal traffic corridor

Efficient management of traffic corridors is critical for sustaining urban mobility. Exclusive bus lane (EBL) and high occupancy vehicle lane (HOVL) are two prominent strategies for enhancing public transit services and alleviating congestion. EBLs prioritize bus transit by providing dedicated lanes for faster travel times, while HOVLs encourage carpooling by reserving lanes for high-occupancy vehicles. However, static implementations of these policies may underutilize road resources and disrupt general-purpose lanes. Dynamic implementation, based on real-time demand, can potentially maximize road efficiency and minimize negative impacts. This study first compares the mixed traffic policy (MTP), exclusive bus lane policy (EBLP), and high occupancy vehicle lane policy (HOVLP) by formulating the total system costs in the context of a bimodal traffic corridor involving private cars and public buses. Under each lane policy, the bus frequency is optimized together with the modal split equilibrium derived separately. Based on dynamic demand simulated using an Ornstein-Uhlenbeck (O-U) process, switching thresholds are then derived to identify optimal periods for implementing each policy. Results reveal significant reductions in total system costs with the proposed dynamic policy schedules. Compared to static implementations, the dynamic policy schedules achieve cost reductions of 11.9%, 6.70%, and 43.64% relative to MTP-only, EBLP-only, and HOVLP-only scenarios, respectively. Additionally, in two real case studies of existing EBL and HOVL operations in Seattle, the proposed dynamic policy reduces total costs by 32.5% and 28.6%, respectively. The findings provide valuable insights for policymakers and transit planners, offering a robust framework for dynamically scheduling and integrating EBL and HOVL policies to optimize urban corridor efficiency and reduce overall system costs.

math.OC↗

arXiv2025

Dynamic Switching Models for Truck-only Delivery and Drone-assisted Truck Delivery under Demand Uncertainty

Integrating drones into truck delivery systems can improve customer accessibility, reduce operational costs, and increase delivery efficiency. However, drone deployment incurs costs, including procurement, maintenance, and energy consumption, and its benefits depend on service demand. In low-demand areas, drone-assisted trucks may underutilize resources due to high upfront costs. Accurately predicting demand is challenging due to uncertainties from unforeseen events or infrastructure disruptions. To address this, a market entry and exit real option approach is used to optimize switching between truck-only and drone-assisted delivery under stochastic demand. Results show that deploying multiple drones per truck offers significant cost advantages in high-demand regions. Using the proposed dynamic switching model, deterministic and stochastic approaches reduce costs by 17.4% and 31.3%, respectively, compared to immediate cost-saving switching. Sensitivity analysis reveals asymmetric effects of stochastic parameters on entry and exit timings. A stochastic multiple-options model is further developed to dynamically switch between truck-only and drone-assisted delivery with varying drone numbers. Applying these models to Miami-Dade County, we evaluate dynamic switching costs for three major logistics operators. This study highlights the potential benefits of dynamic delivery switching and provides insights for optimizing logistics operations.

eess.SY↗