The Volume-Based Pollution-Routing Problem with Time Windows: A Case Study

Green logistics has gained significant attention in recent years due to increasing pollution levels and their negative effects. This area of research is crucial as governments and countries worldwide recognize the severity of pollution and its detrimental effects. Despite progress, significant gaps remain due to the lack of advanced models that consider additional factors and the influence of speed on their outcomes. This paper presents a case study on the Volume-based Pollution-Routing Problem with Time Windows (VPRPTW). The objective is to minimize CO⁢2 emissions and improve customer satisfaction using a fleet of delivery vehicles. We propose a mathematical model and a probabilistic Tabu Search (TS) algorithm to solve the studied VPRPTW. The study revealed a decrease in daily fleet size from 16 to 12, indicating improved operational efficiency. In our study, we evaluate the impact of vehicle speed on fuel consumption and compare the results with a constant route speed to those obtained at varying speeds. Computational experiments reveal a significant difference of over 20% between fixed and variable speed assumptions. Additionally, we confirm that distance alone does not always correlate with energy consumption and CO⁢2 emissions. This highlights the importance of considering variable speeds in routing problems to assist logistics companies, urban planners, and policymakers achieve more accurate and environmentally friendly transportation solutions.