Sustainable Waste Management: Enhancing Efficiency with Vehicle Routing Optimization Techniques

Effective waste management is crucial for advancing sustainability on university campuses. This study use advanced optimization approaches to examine and improve waste collection routes, with the objective of dramatically enhancing truck routing efficiency and overall waste management efficacy. The research is divided into two unique scenarios: the first emphasizes the optimization of vehicle routes based on designated waste collection places for each truck, while the second enhances routes by incorporating truck capacity limitations through the employment of private company cars. To evaluate the efficacy of these improvements, the aggregate transportation distances of existing garbage collection routes are juxtaposed with those refined by four methodologies: the Savings Algorithm, the Nearest Neighbor Method, Microsoft Excel Solver, and VRP Spreadsheet Solver. The findings indicate that in the initial scenario, privately owned automobiles enhanced by these techniques attained the minimal overall transit distance of 17.310 kilometers. Conversely, universityowned trucks achieved optimal distances of 4.852 kilometers for Truck 1 and 5.770 kilometers for Truck 2. In the second instance, the optimized routing exhibited its effectiveness with a total transit distance of 20.300 kilometers. These findings highlight the potential of utilizing advanced routing algorithms to minimize transportation distances, therefore improving operational efficiency, decreasing fuel consumption, and promoting more sustainable waste management practices in educational institutions. This study presents a comparative analysis of various optimization techniques, offering a comprehensive framework that can be tailored to tackle analogous logistical challenges in diverse institutional contexts, in accordance with the overarching goals of improving information technology and operational strategies within Computer Science.