Mathematical Model for Optimizing Green Waste Recycling Networks Considering Outsourcing

The rapid growth of industry and economy and the increase in incomes have led to the influx of people to big cities and thus a sharp increase in waste production. Inappropriate waste management damages city infrastructure and affects community health and environment. Governments need to plan and implement integrated management from waste production to final disposal for achieving sustainable solution. This paper presents a bilevel multiobjective programming model for the design and planning of a municipal solid waste management (MSWM) network. The MSWM network includes production sites, transfer stations (TSs), treatment centers (TCs), waste recycling centers, and landfill sites. The municipality outsources waste through auctions. The Stackelberg game method is used in the context of a bilevel problem for the design of an MSWM network in auction conditions. The municipality, as the primary decision maker (DM), decides on the locations of TCs, TSs, and landfills, the technology type and capacity of TSs and treatment facilities, as well as on waste outsourcing and selection of the winning company. The bidders as followers set their bids in a way that maximizes their profit and winning chance at the auction. The proposed model is transformed into a single-level multiobjective mixed-integer linear programming (MOMILP) model using the Karush-Kuhn-Tucker conditions. Then, the augmented e-constrained method is used to solve the multiobjective model. A real case study in the Qazvin province of Iran is conducted to show the applicability of the proposed approach. The results show that the presented MOMILP model is useful in designing an integrated MSWM network trading off between total costs and total greenhouse gas emission based on the main DM priorities.