# Urban Logistics through River: A Two-Echelon Distribution Model
## 5 Conclusions  
The popularity of the Internet and social networks, followed by historical and disruptive events like the COVID-19 pandemic, have reinforced the increase of online shopping, generating an expansion of e-commerce. Many retail stores had to rethink their operations and start offering online sales channels to catch up with the trend, expand their boundaries and be able to maintain their sales despite the restrictions imposed, delivering the ordered products to their customers' homes. Due to the considerable increase in demand, delivery companies have had to rethink their logistics and supply chain management operations to provide efficient last-mile delivery, as this activity is the core of e-commerce delivery operations. The most common distribution systems applied in urban logistics are two-echelon delivery networks. The two-echelon distribution network has an Urban Distribution Center or depot located outside the town, and from this facility, the parcels are distributed to a set of Urban Consolidation Centers or satellites that are located inside the cities and are such a cross-docking facility to distribute the parcels to a geographically dispersed customer (last-mile delivery). This paper studied the problem of designing delivery routes in two-echelon distribution networks. An approximation algorithm with a three-stage decomposition strategy was implemented dealing with the computational complexity of the problem: (1) a 2D-\(k\)-means clustering procedure is performed to allocate the customers to the closest satellite, (2) to find the second echelon routes, (3) is the first echelon routing. The two last stages were solved by the implementation of an approximation algorithm based on the NN routing heuristic. A small-size instance (50 nodes) taken from a dataset that contains delivery points of a real-life French company was used for the experiment. Two different scenarios were proposed in which a heterogeneous fleet of delivery vehicles was evaluated using multi-modal transportation. We use inland waterway transportation (barge), delivery vans, and e-cargo bikes. The performance of the delivery networks proposed was assessed. Results show that the consideration of environmental-friendly transportation modes has a great potential to reduce some of the issues and externalities caused by conventional urban parcel delivery systems. In this specific study, the least polluting means of transportation is the barge. Moreover, this means of transportation has cheaper costs -fixed costs and costs of energy consumption- than those associated with the van. To sum up, the fixed costs decrease by 41% and energy consumption by 92% when applying a river transportation mode and e-cargo bikes in the first and second echelon, respectively, of the distribution network (scenario 1 versus scenario 2). It is important to note that the scenario that involves the use of inland waterways for parcel distribution is very useful because waterways are much less congested than Parisian city roads. However, thinking about further applications and tests in different cities, there are different aspects to be considered. First, there can be certain periods of the year when the river may not be navigable; in those cases, scenarios involving vans as a complementary distribution network should be used. In addition, the schedules established for navigation on the river must be taken into account since navigation is not allowed on a continuous daytime basis. Each city, in particular, has its own geography and infrastructure. For example, not all cities are suitable for this type of scenario because waterways are needed for its implementation; furthermore, public policies not only for navigability but also for last-mile distribution may differ. Hence, further studies should consider some additional aspects to analyze the viability of these scenarios in other cities. This research has some limitations that open research avenues. Last-mile logistics is a very complex activity due to different factors, such as the instability of actors.