Smart municipal waste management with source segregation and recovery optimization

Abstract

This study develops an integrated optimization framework for designing a source-segregated municipal solid waste management network. A mixed-integer linear programming model is proposed to determine the optimal configuration of collection stations, assignment of waste generation points, installation of smart monitoring systems, and allocation of waste flows to treatment and recycling facilities within a multi-echelon municipal logistics network. The model minimizes total system cost while satisfying capacity, budget, and recycling constraints. A numerical experiment based on a representative case study of Tabuk city, Saudi Arabia, is conducted to demonstrate the applicability of the model. The results show that the optimal network opens three collection stations and allocates waste efficiently across treatment facilities, achieving a diversion rate of approximately 72% from landfill. The comparative and sensitivity analyses indicate that integrating source segregation with monitoring-enabled operational coordination, optimized infrastructure utilization, and resource recovery can significantly improve economic performance while reducing landfill dependency. Sensitivity analysis reveals that segregation participation, recycling revenue, and disposal cost are key drivers of system performance. Increased participation in source segregation leads to higher recovery rates and improved economic outcomes, while higher recycling revenues and disposal costs promote waste diversion from landfill. The findings highlight the importance of coordinated planning, economic incentives, operational coordination, and public participation in developing sustainable waste management systems. The proposed framework provides a practical decision-support tool for municipalities seeking to transition toward circular economy practices and improve resource efficiency in urban waste management.