Abstract
This study explores various vehicle configurations and waste classification strategies to address the Capacitated Vehicle Routing Problem with Time Constraints (CVRPTC) in waste management. By integrating practical factors such as labor costs and working hours, and utilizing simulated residential and GIS data, the research employs cluster balancing and simulated annealing (CB-SA) algorithms to identify cost-effective solutions. The findings highlight the importance of selecting appropriate vehicle types and routing strategies tailored to specific operational demands. In addition, the study underscores the impact of operational parameters on overall costs and vehicle requirements. These insights provide valuable guidance for waste management companies aiming to enhance efficiency and sustainability in their collection operations through advanced optimization techniques and strategic vehicle selection. From a managerial perspective, the results advocate for region-specific vehicle and routing strategies to optimize resource utilization and cost management. Furthermore, the study emphasizes the necessity of continuously monitoring operational parameters to maintain cost-effectiveness and adapt to evolving waste management needs.