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This bibliometric analysis focuses on the vehicle routing problem (VRP) model in the field of logistics delivery. The study utilizes a comprehensive dataset of 2,000 VRP-related publications obtained from the Scopus database, spanning the years 2007 to 2023. Through the application of bibliometric methods, this research aims to uncover key insights regarding research trends, country contributions, and recent topics within the VRP research network. Various bibliometric indicators, including publication count, author productivity, relevant sources, institutional affiliation, and citation frequency, are employed to conduct the analysis. The findings shed light on the evolution and trajectory of VRP research, while also highlighting noteworthy countries and topics that have received significant attention. This study not only enhances the overall understanding of VRP but also serves as a foundation for future investigations aimed at enhancing the efficiency and effectiveness of logistics delivery. [ABSTRACT FROM AUTHOR]

2E-MDCVRP is a multi-depot, capacity, twoechelon vehicle routing issue. Satellites make it possible to collect and sort orders. In this paper, a 2E-MDCVRP model will be designed to be applied to e-commerce. In the completion stage, the researcher developed a 2E-MDCVRP solution with two stages of completion. The first stage is finding the best route for the satellite to travel to the customer. In the first stage of work, satellites are plotted as centroids in clusters using the k-Means algorithm to obtain k-set clusters. To determine route scheduling using the RNN algorithm in determining travel routes in the second echelon. The second stage uses the trial-anderror method to determine the first echelon's routing schedule. This research aims to minimize the operational application, fuel consumption, vehicle maintenance, vehicle oil change, and handling costs. Moreover, at the end of the paper, the researcher simulate the model that has been built and test the model's effectiveness by comparing it with the classic MDCVRP model, which is similar to the Same-Day Delivery model. The test results show that the 2E-MDCVRP model can make better total distance and cost improvements than the classic MDCVRP model carried out by Same-day Delivery. [ABSTRACT FROM AUTHOR]

Background: The rise of e-commerce in the community makes competition between logistics companies increasingly tight. Every e-commerce application offers the convenience and choices needed by the community. The Two-Echelon Vehicle Routing Problem (2E-VRP) model has been widely developed in recent years. 2E-VRP makes it possible for customers to combine shipments from several different stores due to satellites in their distribution stream. The aim of this paper is to optimize a two-echelon logistics distribution network for package delivery on e-commerce platforms, where vans operate in the first echelon and motorcycles operate in the second echelon. The problem is formulated as 2E-VRP, where total travel costs and fuel consumption are minimized. This optimization is based on determining the flow in each echelon and choosing the optimal routing solution for vans and motorcycles. Methods: This paper proposes a combination of the K-means Clustering Algorithm and the 2-opt Algorithm to solve the optimization problem. Many previous studies have used the K-means algorithm to help streamline the search for solutions. In the solution series, clustering is carried out between the satellite and the customer in the first echelon using the K-means algorithm. To determine the optimal k-cluster, we analyzed it using the silhouette, gap statistic, and elbow methods. Furthermore, the routing at each echelon is solved by the 2-opt heuristic method. At the end of the article, we present testing of several instances with the different number of clusters. The study results indicate an influence on the determination of the number of clusters in minimizing the objective function. Results: This paper looks at 100 customers, 10 satellites, and 1 depot. By working in two stages, the first stage is the resolution of satellite and customer problems, and the second stage is the resolution of problems between the satellite and the depots. We compare distance and cost solutions with a different number of k-clusters. From the test results, the number of k-clusters shows an effect of number and distance on the solution. Conclusions: In the 2E-VRP model, determining the location of the cluster between the satellite and the customer is very important in preparing the delivery schedule in logistics distribution within the city. The benefit is that the vehicle can divide the destination according to the location characteristics of the satellite and the customer, although setting the how many clusters do not guarantee obtaining the optimal distance. And the test results also show that the more satellites there are, the higher the shipping costs. For further research, we will try to complete the model with the metaheuristic genetic algorithm method and compare it with the 2-opt heuristic method. [ABSTRACT FROM AUTHOR]