Logistic Modeling of the Last Mile: Case Study Santiago, Chile

Abstract

This research proposes a new distribution system of goods in the historical center of the city of Santiago, Chile. For the design of the urban logistic system, the methodology city logistics and last mile are used. This design incorporates to the freight transport flexible solutions that improve the efficiency of the distribution process and trade supply, minimizing the environmental impact of the atmospheric pollution (AP). The proposal was made through the data collection, the characterization of the sector and the diagnosis of the urban logistics processes. The analysis of the factors allowed to evaluate the costs of the AP negative externalities. The causes were used as design criteria for the proposals, with the aim of improving the quality of life of the city users. The physical location selection of the Cross-Docking was made through an optimization model of maximum coverage. The optimization algorithm of the nearest neighbor was proposed for vehicle routing. The analytic hierarchy process (AHP) was used to generate a ranking of the best non-polluting vehicles to be used in the zone. Finally, the results obtained allowed a 53 ton decrease in carbon dioxide in the square kilometer and reduced 1103 h of interruptions per year in the vehicular congestion of the sector.

Impact of Logistics Capacity on Economic Sustainability of SMEs

“…This research helps in partial closing of the research gap regarding impact of logistics capacities on economic sustainability of companies. Some similar attempts concerning this topic were previously made by Zimon and Zimon [62], regarding the influence of logistics on profitability, as well as by Green [63], with a study of logistics performance and its impact on marketing and financial performance. This research expands on these studies, by focusing on eight key business factors in the SME environment, such as position within a supply chain, export location and form, sales share, and number of supply chains.…”

Use of artificial intelligence in last mile delivery

“…New last mile concepts include: deliveries using drones or small ground autonomous robots launched from trucks, distribution of goods by electric vehicles, deliveries to the trunk of parked cars, combined distribution of freight transport with public and private vehicles, reverse logistics, crowdsourcing of deliveries or mobile lockable cabinets. [4,5,6] With the growing digitalization of the logistics industry, more and more companies are also starting to use artificial intelligence. They use it in their logistics and supply chain to reduce the amount of time and money they have to spend on finding out how, when and where to deliver a good or service.…”

The Logistics Service Mode Selection for Last Mile Delivery Considering Delivery Service Cost and Capability

“…The related parameters and their values for delivery service capacity of branch B new in YD Express. According to Equations (17)- (20), the delivery service capabilities of each aspect can be obtained, i.e., A B = 260, A R = 280, A T = 260, and A I = 255, respectively.…”

“…In reality, in the process of logistics service mode selection for last mile delivery, express enterprises need to pay attention to some impact factors [18][19][20][21][22][23][24][25][26][27]. For example, Jing [18] focused on the impacts of vehicle matching degree and transportation factors on the delivery service cost, Koetse et al [19] focused on the impacts of extreme weather and natural disasters, Urzua-Morales et al [20] proposed a flexible freight transport solution that improves delivery service efficiency and minimizes the environmental impact of the atmospheric pollution. Nemoto [21] focused on information technology factors and show that the application of ICT can reduce the complexity of logistics operations and improve the operation efficiency.…”