Enabling the freight traffic controller for collaborative multi-drop urban logistics: practical and theoretical challenges

There is increasing interest in how horizontal collaboration between parcel carriers might help alleviate problems associated with last-mile logistics in congested urban centers. Through a detailed review of the literature on parcel logistics pertaining to collaboration, along with practical insights from carriers operating in the United Kingdom, this paper examines the challenges that will be faced in optimizing multicarrier, multidrop collection, and delivery schedules. A “freight traffic controller” (FTC) concept is proposed. The FTC would be a trusted third party, assigned to equitably manage the work allocation between collaborating carriers and the passage of vehicles over the last mile when joint benefits to the parties could be achieved. Creating this FTC concept required a combinatorial optimization approach for evaluation of the many combinations of hub locations, network configuration, and routing options for vehicle or walking to find the true value of each potential collaboration. At the same time, the traffic, social, and environmental impacts of these activities had to be considered. Cooperative game theory is a way to investigate the formation of collaborations (or coalitions), and the analysis used in this study identified a significant shortfall in current applications of this theory to last-mile parcel logistics. Application of theory to urban freight logistics has, thus far, failed to account for critical concerns including (a) the mismatch of vehicle parking locations relative to actual delivery addresses; (b) the combination of deliveries with collections, requests for the latter often being received in real time during the round; and (c) the variability in travel times and route options attributable to traffic and road network conditions

Shipping exchange analysis of outsourced parcel shipping to LTL carriers

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 31-32).There is a large and intricate network of trucks, warehouses, stores, and companies that support the transportation and logistics industries in the United States. Different categories of carriers transport shipments of all sizes by utilizing complex tracking systems. Further, there is a network of brokers, consultants, third-party and fourth party logistics providers who organize and integrate these resources and services to provide transportation solutions for any shipment challenge. Solutions are created by integrating the capabilities of several carriers and other transportation service providers. Based on this integration, this thesis proposes a business model that will leverage the existing transportation network in US to provide a low-cost shipping option for residential shippers. It is concluded that the business model is possible with strong industry expertise and powerful database development.by Jamie K. Curran.S.B

Data driven spatio-temporal analysis of e-cargo bike network in Lisbon and its expansion: The Yoob case study

The adoption of more environmentally friendly and sustainable fleets for last-mile parcel delivery within large urban centers has been on the rise. Cargo bikes have been the most common alternative. The implementation of this type of fleet has proven to bring benefits, but has evidenced some limitations. The infrastructure network, which supports urban logistics, had to adapt to respond to the requirements of this new type of fleet. The implementation of micro-hubs and nano-hubs was the solution. Our study has two main objectives. The first objective is to perform a spatiotemporal characterization of fleet behavior, by conducting a case study where we explored the data from YOOB (a last mile delivery logistics start-up that operates in the Lisbon area and outskirts) e-cargo bike fleet. And the second is to identify potential expansion locations to the establishment of new hubs. The work procedures followed the CRIPS-DM methodology and the collected data was based on a 4-month period (January to April 2022). By adopting data science and machine learning techniques, five types of performances of YOOB fleet were identified, with variations in distances traveled, times, volumes transported and speeds. In the perspective of expanding YOOB's e-cargo bike network, three new locations in Lisbon were signaled for potential new hub installation.A adoção de frotas mais ecológicas e sustentáveis para a distribuição das encomendas na última milha dentro dos grandes centros urbanos tem vindo a crescer. As bicicletas de carga têm sido a alternativa mais comum. A implementação deste tipo de frotas, demonstrou trazer benefícios, mas evidenciou algumas limitações. A rede de infraestruturas, que serve de suporte á logística urbana, teve de se adaptar para poder responder às necessidades deste novo tipo de frotas. A implementação de microhubs e nano-hubs foram a alternativa. O nosso estudo tem dois objetivos principais. O primeiro objetivo é o de fazer uma caracterização espácio temporal dos comportamentos da frota, através de um estudo de caso onde efetuámos a exploração dos dados da frota de e-cargo bike da YOOB (start-up logística de entregas na última milha que atua na área de Lisboa e na periferia). E o segundo consiste em identificar potenciais locais de expansão para a instalação de novos hubs no mesmo estudo de caso. Nos processos de trabalho foi seguida a metodologia CRISP-DM e os dados recolhidos foram referentes a um período de 4 meses (Janeiro a Abril de 2022). Com recurso a técnicas de ciência dos dados e aprendizagem automática, foram identificados cinco tipos de desempenhos da frota da YOOB, com variações em distâncias percorridas, tempos efetuados, volumes transportados e velocidades praticadas. Numa perspetiva de expansão da rede de e-cargo bike da YOOB, forma identificados três novos locais na cidade de Lisboa para a instalação potencial de novos hubs

The effect of customer satisfaction on parcel delivery operations using autonomous vehicles: An agent-based simulation study

The quality of Third-Party Logistics (3PL) services represented by delivery time decides the outcome of customer satisfaction. The result of this satisfaction judges the type of Word of Mouth (WoM) that, if positive, plays a vital role in attracting non-customers who are willing in 3PL services to join as customers. In this paper, we investigate the effect of an essential factor represented by Word of Mouth on the number of customers in 3PL companies. Therefore, an agent-based model for parcel delivery is developed to investigate the impact of social factors such as WoM and other operational factors, including vehicle number and speed, on customer number and satisfaction, average service time, and vehicle utilization. As a methodology, state charts of Vehicle, Customer, Hub agents are developed to mimic the messaging protocols between these agents under the WoM concept. A case study based in 3PL in Jordan is used as a test bench of the developed model. A sensitivity analysis study is conducted to test the developed model's performance, including different levels of influential model parameters such as targeting non-customers parameters by Loyal/Unhappy customers. Key results reveal that the best scenario is achieved when the WoM value equals 10, the vehicle number equals 30, and the vehicle speed equals 60 km/h. These model parameters result in higher customer numbers of 873, vehicle utilization equals 63%, and customer satisfaction equals 99%. Video of our proposed model showing it in action can be found at: https://www.youtube.com/watch?v=3rR4l130-QU

Parcel lockers vs. home delivery: a model to compare last-mile delivery cost in urban and rural areas

Purpose This paper investigates the economic performances of two business-to-consumer (B2C) e-commerce last-mile delivery options -parcel lockers (PLs) and traditional home delivery (HD) in contexts where e-commerce is still at its early stages. It analyses and compares two different implementation contexts, urban and rural areas. Design/methodology/approach This study develops an analytical model that estimates delivery costs for both the PL and HD options. The model is applied to two base cases (representative of urban and rural areas in Italy), and sensitivity analyses are subsequently performed on a set of key variables/parameters (i.e. PL density, PL fill rate and PL annual costs). To support the model development and application, interviews with practitioners (Edwards et al., 2011) were performed. Findings PLs imply lower delivery cost than HD, independently from the implementation area (urban or rural): advantages mainly derive from the higher delivery density and the drastic reduction of failed deliveries. Benefits entailed by PLs are more significant in rural areas due to lower PL investments and annual costs, as well as higher HD costs. Originality/value This paper offers insights to both academics and practitioners. On the academic side, it develops a model to compare the delivery cost of PL and HD, which includes the analysis of urban and rural contexts. This could serve as a platform for developing/informing future analytical/optimisation contributions. On the managerial side, it may support practitioners in making decisions about the implementation of PLs and HD, to benchmark their costs and to identify the main variables and parameters at play

Mixing quantitative and qualitative methods for sustainable transportation in Smart Cities

L'abstract è presente nell'allegato / the abstract is in the attachmen

The Two-Echelon Vehicle Routing Problem with Pickups, Deliveries, and Deadlines

This paper introduces the Two-Echelon Vehicle Routing Problem with Pickups, Deliveries, and Deadlines (2E-VRP-PDD), a new and emerging routing variant addressing the operations of logistics companies connecting consumers and suppliers in megacities. Logistics companies typically organize their logistics in such megacities via multiple geographically dispersed two-echelon distribution systems. The 2E-VRP-PDD is the practical problem that needs to be solved within each of such a single two-echelon distribution setting, thereby merging first and last-mile logistics operations. Specifically, it integrates forward flow, reverse flow, and vehicle time-synchronization aspects such as parcel time windows, satellite synchronization, and customer-dependent deadlines on the arrival of parcels at the hub. We solve the 2E-VRP-PDD with a tailored matheuristic that combines a newly developed Adaptive Large Neighborhood Search (ALNS) with a set-partitioning model. We show that our ALNS provides high-quality solutions on established benchmark instances from the literature. On a new benchmark set for the 2E-VRP-PDD, we show that loosening or tightening time restrictions, such as parcel delivery deadlines at the city hub, can lead to an 8.5% cost increase; showcasing the overhead associated with same-day delivery compared to next-day delivery operations. Finally, we showcase the performance of our matheuristic based on real-life instances which we obtained from our industry collaborator in Jakarta, Indonesia. On these instances, which we share publicly and consists of 1500 - 2150 customers, we show that using our ALNS can significantly improve current operations, leading to a 17% reduction in costs