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    A Nonlinear Programming Model for Long-Term Planning of Municipal Solid Waste Management Systems: The Desire for Global Optima
    (Springer, 2024) Kucukoglu, Ilker; Korucu, Mahmut Kemal
    Long-term planning of municipal solid waste management systems (LPMSWMS) is a multi-layered problem that seeks answers to different decisions (i.e., method selection for the collection, transfer, treatment, and disposal of wastes, technology selection for the methods, capacity selection for the technologies, location selection for the processes, and allocation of the waste masses between locations). Since each of these decision layers has a dynamic impact on the others, all decision layers must be evaluated simultaneously in order to achieve the most accurate and effective results for the LPMSWMS. On the other hand, it is difficult to develop a mathematical model that can evaluate all decision layers simultaneously due to the complexity of the problem. Hence, almost all existing cost optimization models proposed for the LPMSWMS use a multi-step approach for the decision layers that restricts the mass balance of the waste by assuming all layers are independent from each other. However, such approaches may lead to giving up on the global optimality for the models. In this context, this study introduces a new mixed-integer nonlinear programming model for the LPMSWMS that provides an integrated mass balance for the waste streams. Regarding the current technological condition of municipal solid waste management systems, the proposed model provides integrated decisions for the LPMSWMS considering the location, technology, capacity, and waste flow plans. The proposed optimization model was tested at various spatial and temporal scales for the Bursa province of T & uuml;rkiye. The optimal results obtained for the model clearly show that this new model may be the first nonlinear mathematical model capable of overcoming the above-mentioned mathematical challanges. This new model has the potential to be easily used for any region of the world and to give decision-makers the most appropriate system option for all decision layers simultaneously, as long as the site-specific waste management parameters required by the model are correctly configured.
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    Öğe
    A two-stage optimization approach for big-scale problems in long-term planning of municipal solid waste management systems
    (Springer, 2025) Korucu, Mahmut Kemal; Kucukoglu, Ilker
    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.