This paper introduces a decentralized framework for the dynamic management and optimization of waste collection fleets. Combining distributed multi-agent coordination, dynamic optimization, and digital twin technologies, this framework not only promises significant reductions in operational costs and environmental impact but also enhances real-time responsiveness to disruptions. We detail the architecture and functionality of the proposed system, which includes real-time monitoring, simulation of truck movements, and the distributed and adaptive coordination of routes based on real-time data. Our preliminary simulation results show promise of monitoring and controlling routes of large fleets in daily waste container collections, decreasing operational expenses, thereby advancing the state of urban waste management.