Transportation Route Optimization of Municipal Solid Waste Based on Improved Ant Colony Algorithm in Internet of Vehicles

In smart city, the internet of vehicles provides technical support and innovative power for the development of municipal solid waste management system by virtue of the deep integration of information technology and vehicles. The vehicle routing problem based on waste classification for collection and transportation (C&T) has garnered increasing attention as a typical issue within this system. Given the diverse nature of waste types and the need to organize multiple vehicles to service collection points, congestion often arises due to simultaneous vehicle operations or queuing, posing a significant challenge. To address this, our study introduces asynchronous constraints on vehicle operations to mitigate congestion. Furthermore, building upon the separate loading and unified loading waste C&T models, a combined C&T model grounded in waste classification is devised. We propose an enhanced ant colony optimization algorithm to solve this intricate problem and validate its efficacy. Experimental findings reveal that, compared to both separate and unified schemes, the proposed combined model yields respective reductions of 5.38% and 2.75% in C&T costs. Meanwhile, the comprehensiveness of the combined model has been demonstrated through other experiments, providing a reference for the improvement and optimization of garbage classification C&T schemes.