This article presents a novel algorithm based on the cluster first-route second method, which executes a solution through K-means and Optics clustering techniques and Nearest Neighbor and Local Search 2-opt heuristics, for the solution of a vehicle routing problem with time windows (VRPTW). The objective of the problem focuses on reducing distances, supported by the variables of demand, delivery points, capacities, time windows and type of fleet in synergy with the model's taxonomy, based on data referring to deliveries made by a logistics operator in Colombia. As a result, good solutions are generated in minimum time periods after fulfilling the agreed constraints, providing high performance in route generation and solutions for large customer instances. Similarly, the algorithm demonstrates efficiency and competitiveness compared to other methods detailed in the literature, after being benchmarked with the Solomon instance data set, exporting even better results.

With globalization and the expansion of cities, the movement of goods and people has significantly increased, both economically and socially. This sector serves as a vital component of any economy, fostering economic and social development. However, its detrimental effects pose significant challenges for countries seeking to pursue sustainable development policies. Being one of the most energy-intensive sectors, it emits greenhouse gases and pollutants, contributing to environmental degradation and noise pollution. While increased traffic and mobility offer benefits, they also strain resources and lead to higher energy consumption. The primary objective of this article is to assess the sustainability of freight transport in the Moroccan city of Fez and propose supportive solutions for various stakeholders in urban logistics. This involves examining the complex relationship between different factors and the sustainability of Urban Freight Transport (UFT), including accessibility, congestion, road occupancy, environmental impacts, health impacts, and road safety. The research data were collected from 100 managers and employees of logistics and transportation companies in Morocco. Structural equation modeling was utilized to test and confirm the hypotheses and the research model. The results of these analyses demonstrated a positive impact relationship between the various factors and the sustainability variable. Subsequently, we suggest the establishment of delivery areas and an urban distribution center as two sustainable logistics solutions. The analysis and its findings can be applied to any other city.