Rescheduling Multiproduct Delivery Planning With Digital Technologies for Smart Mobility and Sustainability Goals

In this article, we study a load-dependent vehicle routing problem (LDVRP) to devise a delivery plan for vehicles carrying various types of products (with different quality and rejection rates) to deliver at the lowest cost and environmental impact. Therefore, this study develops a multidepot, multiproduct, multivehicle model considering the demands of customers, rejection rates of products, predefined time windows, speed limits, and extra waiting time. To manage the complexity of such a system, digital technologies support the decisions since the systems' conditions are dynamic and vary in an uncontrollable way. For example, unexpected changes in traffic require the support of digital technologies to properly handle a full rescheduling by changing both the vehicles' speed and the waiting time. In terms of sustainability aspects, these decision variables affect carbon dioxide emissions, customers' satisfaction, and delivery costs. The proposed model will be discussed mathematically and solved using a Genetic Algorithm. Finally, different numerical examples reveal how smart mobility sets the proper decisions and solves the tradeoffs emerging from the analysis of environmental, social, and economic sustainability.

Automated summary

In this article, the Load-Dependent Vehicle Routing Problem (LDVRP) is studied to develop an optimal delivery plan for vehicles carrying different types of products. The model takes into account various factors such as customer demands, rejection rates of products, time windows, and speed limits. Digital technologies are used to support decision-making due to the dynamic nature of the system. The proposed model is mathematically discussed and solved using a Genetic Algorithm, leading to sustainable solutions balancing environmental, social, and economic aspects.