Optimal site selection and location-routing for a sustainable integrated solid waste management system

This study aims to provide a decision support framework for designing a sustainable Integrated Solid Waste Management (ISWM) system. Sustainability of the ISWM system is addressed by incorporating economic, environmental and social objectives. The proposed study focuses on the issues of location selection, routing and waste flow to optimise the system. To address the location selection problem, Multi-Criteria Decision Making (MCDM) methods are utilised in novel frameworks under the Geographic Information System (GIS) environment. The methods of Analytic Hierarchy Process (AHP), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the Decision Making Trial and Evaluation Laboratory (DEMATEL) are employed to propose two hybrid methods in adaptive frameworks: AHP-TOPSIS and AHP-DEMATEL. To verify the effectiveness of the proposed MCDM methods, these methods are tested with a case of New South Wales (NSW), Australia. The locations found by the MCDM methods can serve as an input (i.e. alternative locations for siting the system’s components) for the holistic optimisation models in the frame of Location-Routing Problem (LRP). To concurrently optimise location selection and waste allocation in the system, an Operation Research (OR) technique, specifically Mixed-Integer Linear Programming (MILP) is utilised to develop novel mathematical models in the frame of LRP. To address the NP-hardness (non-deterministic polynomial-time hard) of the problem, heuristic methods are developed in novel frameworks. The developed models are successfully applied to real-life cases in NSW and Tehran, Iran to provide a consolidated plan for supporting MSW management systems. The results obtained by the proposed heuristic methods are also validated by comparing them with the exact results obtained by the MILP model. Further, this research has developed an integrated method (i.e. integration of MCDM and MILP models) by proposing a novel multi-dimensional modelling ap