Operations management in distribution networks within a smart city framework

Area of Science:

• Operations Research
• Sustainable Logistics
• Urban Transportation Systems

Background:

• Growing demand for sustainable urban transport necessitates efficient logistics.
• Traditional vehicle routing problems often overlook environmental impacts and urban constraints.
• E-commerce growth increases the complexity of last-mile delivery in smart cities.

Purpose of the Study:

• To address the vehicle routing problem with environmental constraints for sustainable urban transport.
• To develop and validate a model minimizing both delivery costs and pollution.
• To provide insights for fleet planning and vehicle selection in urban logistics.

Main Methods:

• Formulation of a mixed-integer linear programming model for the vehicle routing problem.
• Experimental validation using real-world data from a grocery company in Genoa smart city.
• Tailoring the vehicle routing problem model to include environmental factors and street limitations.

Main Results:

• The proposed model effectively integrates cost minimization and pollution reduction in vehicle routing.
• Real-world data application demonstrates the model's practical utility for fleet planning.
• Commercial distribution strategies show superior business and environmental outcomes when smart mobility is integrated.

Conclusions:

• Integrating environmental constraints and smart mobility goals into distribution models is crucial for sustainable urban transport.
• Optimized routing and fleet composition can lead to significant cost savings and reduced pollution.
• The study provides a practical framework for businesses operating in urban environments to enhance sustainability.