Green Capacitated Vehicle Routing Problem under Traffic Congestion

Abstract

The transportation system has grown significantly and quickly in the past few years. This growth is natural to the development of societies, producing positive externalities that support the economic growth of the regions ‘activities, but it also brings about negative externalities, particularly Traffic congestion. Congestion substantially increases fuel consumption and carbon emissions, exacerbating environmental challenges. This paper introduces a novel approach to model and resolve the Green Capacitated Routing Problem (GCVRP), incorporating traffic congestion and CO2 emissions. Objectives are to minimize the total travelled distance and the associated carbon emissions. This bi-objective problem is NP hard. We propose to convert it to a mono-objective one. The proposed model transforms real distance metrics into a virtual distance adjusted to account for CO2 emissions and congestion levels. Exact solution methods is applied for finding optimal solutions using CPLEX solver with AMPL programming language. Using numerical experiments, the comparison between the real model and the suggested virtual model shows that the new methodology improves computing efficiency and solution quality. These results demonstrate how the model can help make more sustainable and efficient decisions about transportation logistics.