## 1 Introduction  
The volume of e-commerce deliveries has witnessed significant growth in recent years, reaching a staggering USD 5.2 trillion in digital platform product sales during 2021. It is projected to surge by 56% in the coming years, reaching approximately USD 8.1 trillion by 2026 [1]. This substantial upswing not only reshapes the dynamics of commerce by shifting the delivery profile from a scenario of few customers with large volumes to many customers demanding small packages, but also poses intricate challenges on logistics, particularly in the efficient delivery of goods, especially within major urban centers, where there is heavy traffic and various limitations that reduce delivery efficiency. This, along with the increase in express orders, deliveries outside regular business hours, and the demand for rapid services underscore the need for an innovative logistics approach [2, 3].  
A potential solution to these challenges involves the utilization of small Urban Transshipment Points (UTPs) or Urban Distribution Satellites for the two-echelon capacitated vehicles routing problem (2E-CVRP). This strategy is essential for effectively managing the final delivery stage, often referred to as the last mile, and requires swift and strategic responses to optimize routes, reduce costs, and address complex urban variables. The concept of the 2E-CVRP involves dividing the final product delivery process in large urban centers into two levels, utilizing intermediate facilities (satellites) and different types of vehicles in the process [4]. The core concept is to use larger freight vehicles to consolidate large quantities of packages and transport them efficiently from the distribution center to the satellite, which is then responsible for completing the final delivery to customers using smaller urban vehicles, further streamlining the process [5].  
Despite its benefits, the 2E-CVRP is an NP-hard problem and presents significant computational complexity, making efficient problem-solving a challenge [6]. This challenge is amplified when it must be implemented in systems that require quick responses, such as interactive Decision Support Systems (DSS), which are very useful for enhancing operations and providing training for logistics professionals and students to sharpen their intuition and improve their critical senses [7]. This is because interactive DSS must offer quick, efficient, and reliable responses [8]. However, achieving this requires the use of rapid and acceptable approximation techniques, with defined limits for compute time and solution quality [9]. For truly interactive decision support, computation times of less than a minute for group settings and less than 30 s for individual user settings are a typical minimum requirement, while real-time response is preferred [10].  
Consequently, this study focuses on developing a heuristic designed to address the two-echelon capacitated vehicle routing problem (2E-CVRP). The specific aim is to integrate it into decision support systems for teaching and training logistics professionals in e-commerce and students. The proposed heuristic relies on local search operators, emphasizing the fundamental principles of this approach. Criteria for evaluating the heuristic center on operational efficiency, measured by resolution speed, while maintaining high-quality solutions.  
Performance analysis of the heuristic involves benchmarks, including instances recognized in the literature as references. The evaluation extends to the practical application of the heuristic in solving real-world problems, utilizing data from a significant e-commerce retailer in Brazil. Thus, this work not only advances the approach to 2E-CVRP through the development of an effective heuristic, but also contributes to e-commerce logistics education, promoting operational efficiency without compromising solution quality.