Robust routing optimization for vehicle routing problem with stochastic demands and time windows: Considering uncertainty and time constraints in logistics planning

Nunez Ruiz (Universidad De Malaga, Spain)
Zofio Barbero (Universidad De Malaga, Spain)

International Journal of Enterprise Modelling
Vol. 16 No. 2 (2022): May: Enterprise Modelling

This research addresses the challenge of robust routing optimization in the context of the Vehicle Routing Problem (VRP) with stochastic demands and time windows. The objective is to develop an effective logistics planning approach that considers demand uncertainty and time constraints in order to minimize costs and improve operational efficiency. A mathematical formulation is presented to model the problem, considering a robustness parameter to account for uncertainty in demand scenarios. The formulation incorporates binary decision variables to determine the routing plan and meet customer demands within specified time windows. A numerical example is provided to illustrate the application of the model, highlighting the impact of uncertainty and time window compliance on the routing plan and total expected cost. The results demonstrate the potential benefits of employing robust routing optimization, providing insights for logistics planners and decision-makers in designing more resilient and cost-effective routing strategies. Further research can explore advanced algorithms and real-world case studies to validate and enhance the proposed approach in practical logistics scenarios