A two-stage optimization approach for big-scale problems in long-term planning of municipal solid waste management systems

Most optimization models developed to solve the long-term planning of municipal solid waste management system (LPMSWMS) problems have some disadvantages, such as the inability to model the problem realistically and the failure of the final decisions to provide global optima due to various mathematical limitations. This study presents an optimization approach for realistically modeling and solving the LPMSWMS problems. This new approach takes into account a non-linear mathematical formulation for the LPMSWMS and solves the model into two main stages. In the first stage, the linear relaxation of the model is used, while the non-linear model formulation is used in the second stage to obtain a more realistic solution for the LPMSWMS. According to the findings, the new optimization approach obtained results for small model volumes in longer times than the reference non-linear model structure. On the other hand, the new approach makes it possible to obtain global optima by producing exact solutions at large model volumes, while the reference non-linear model structure cannot produce any solution. This advantage of the new approach for large model volumes can significantly benefit decision-makers in solving big-scale problems that are likely to be encountered in the real world by giving global optima.