Analysis of the Implementation of an E-Commerce Delivery System

This paper presents an algorithm for the delivery of products from an e-commerce company, with the aim of significantly improving its logistics and organization by focusing on minimizing total delivery hours. The algorithm considers constraints on delivery route capacity and time. A detailed analysis is carried out through queueing models to determine the optimal number of ramps to install and the transport units needed for the efficient transfer of products. These analyses were performed through simulations using real data, considering order size and product purchases modeled through probability distributions, which are used to simulate the demand of a working day. Monte Carlo simulations were also used, in order to generate client groups with simulated demand and fixed capacity. The delivery of products is formulated as a Capacitated Vehicle Routing Problem (CVRP) with time windows. A solution using Ant Colony Optimization (ACO) algorithms was proposed, using a Genetic Algorithm (GA) as a baseline. This algorithm aims to find feasible routes and schedules that meet delivery requirements, considering the constraints. Thus, the CVRP was solved with feasible solutions, significantly reducing total distance traveled and route duration time, compared to the GA. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Analysis of the Implementation of an E-Commerce Delivery System Chapter in Scopus