Last mile deliveries in urban areas cause a disproportionate unsustainable impact, while it is also the most expensive part of the supply chain. This is particularly true for freight flows that are characterized by fragmentation. Logistically, this becomes apparent in vehicles that are driving around with a low vehicle fill rate, leading to the unnecessary presence of freight vehicles in our cities. This study focuses on the operational feasibility of utilizing the spare transportation capacity of a service-driven company as a potential solution to supply small independent retailers, or nanostores. The aim is to reduce inefficient vehicle movement. Based on a real-life implementation, we use SYnchronization Model for Belgian Inland Transport (SYMBIT), an agent-based model, to simulate various bundling scenarios. Results show the total vehicle kilometers and lead times to supply nanostores for the service-driven company to serve its customers. There is a potential to utilize spare capacity to supply nanostores while maintaining a decent service level. The number of vehicle kilometers driven highly depends on the location of the distribution center where the service-driven company operates. Based on these results, the conditions that have to be met to replicate this solution in other urban areas are discussed.
Synchromodal transport incorporates real-time events in a dynamic manner in order to facilitate the most suitable selection of modes, routes and handling points. Up until now, current assessments rely on analytical models. Most of these models average distances for barges and trains via route mapping platforms that provide realistic distances for road only. To reflect on real-world developments more accurately, new thinking and modelling approaches are necessary to bridge academic models with physical transport processes. This paper introduces a computational model which computes movements of agents in geographically referenced space. The model captures stochastic parallel processes for each mode, and simulates decentralized delivery performance of each order in terms of cost, time and emissions at an operational level. Furthermore, we study the routing of individual orders and their responsiveness to disruptions. Computational experiments are performed within a case study which concerns imports of retail goods by unimodal truck transport from France to Belgium. Our findings show that dynamic synchromodal solutions cope with disturbances better, but unnecessary deviations and pro-activeness can also lead to negative effects when compared to static intermodal solutions
The Physical Internet (PI) concept presents a radical change with the aim to revert the unsustainable practices that are used for transporting goods. It identifies dedicated freight flows and transforms them into transparent open logistics networks which can be accessed by other users, such as shippers and carriers. In this paper, we test the universal network openness in which the users can tap into the PI network and place orders that will be assigned to the nearest available transport service and consequently delivered to the order sender. The objective of our paper is to investigate the impact of inserting extra service points into existing dedicated freight flows of a service‐driven company. We simulate different transparency levels and routings to new pickup locations and evaluate the impact in terms of altered lead times, covered distances, and fill rates. The novel aspects presented herein are (1) deliveries based on decentralized location detection of the nearest order sender, (2) dynamically changing speed parameters of agents within specific geographic clusters based on their geo‐locations in order to account for congestion levels, (3) more realistic routing strategies that consider the urban layout, and (4) transparent querying of nearest agents in space and time that meet specific conditions such as current ongoing processes, available capacity, and position. Finally, we identify the impact from a general/holistic perspective that emerges once extra orders are assigned to the service‐driven company's fleet.
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