A bi-level decision framework for strategic planning in urban solid waste management

Urban solid waste management is an increasing global challenge driven by population growth and urbanization. Recycling rates remain below 10% in many developing countries due to inadequate infrastructure and planning. This paper proposes a bi-level programming model to optimize urban solid waste collection and management in a hierarchical supply chain involving transfer stations and specialized treatment facilities. The model captures the decision-making processes of the government, responsible for determining the location of transfer stations and managing waste transportation, and a private company in charge of waste recycling, plant specialization. The upper-level objective, pursued by the government, is to minimize carbon dioxide (CO2) emissions across the supply chain, while the lower-level objective, driven by the private company, seeks to reduce shipping and operational costs. A novel matheuristic algorithm based on a nested local search is developed to solve the bi-level model. The proposed matheuristic incorporates a deconstructive process to generate upper-level solutions. Moreover, bi-level feasibility is ensured by optimally solving the parameterized lower-level problem. Extensive computational experiments were conducted, covering two real-world case studies: Medellín, Colombia, and Santiago, Chile. A budget sensitivity analysis was performed, providing valuable managerial insights into the economic-environmental trade-offs in waste management planning. Furthermore, large-scale instances were tested to evaluate the scalability of the proposed matheuristic. An analysis excluding the private company’s decisions highlighted the advantages of the bi-level approach. The results underscore the potential of the bi-level framework to support strategic decision-making in urban waste management systems, particularly when a hierarchy exists among decision-makers.