Municipal solid waste recycling network with sustainability and supply uncertainty considerations

Abstract

• A stochastic optimization model is developed by explicitly considering sustainability • The developed two-stage stochastic MILP model optimizes the MSW recycling network • The fuzzy best-worst method is used to extend the social life cycle assessment method • The environmental cost is controlled utilizing a well-known risk measure • MRFs, Incinerator, Composting, and LFGRS are sustainable facilities for Mazandaran The stochastic nature of some parameters in a municipal solid waste (MSW) management system justifies the use of stochastic programming models. In this research, a multi-period two-stage stochastic model is formulated as a mixed-integer linear programming model for optimal and sustainable use of MSW by explicitly considering the social, economic, and environmental dimensions of sustainability. The decision variables are categorized into two groups. The first-stage decision variables determine the location, capacity, and type of waste processing plants and facilities. The second-stage decision variables consider transportation, allocation, and distribution of wastes and products. The objective function of the proposed model minimizes various costs of the system. The environmental cost is controlled utilizing a well-known risk measure and to consider the social impacts, the Social Life Cycle Assessment (S-LCA) approach is extended using the fuzzy best-worst method. To handle the uncertainty in the amount of generated waste, a backward scenario reduction method is simulated. Mazandaran province in Iran is selected as a real-life case study to evaluate the performance of the applied method. The assessment of the robustness of the stochastic solution illustrates the significance of using the stochastic model instead of its deterministic one.