Optimization in waste landfilling partitioning in Paraná State, Brazil

In this work, using the concepts of the Facilities Location Problem (FLP), an attempt was made to find the best configuration for clusters of municipalities, referred to here as consortia, for the Municipal Solid Waste (MSW) landfill network in Paraná State, Brazil, which is composed of 399 municipalities. The existing model has a number of deficiencies, including not meeting the entire demand of the state, an excessive number of small landfills and several non-contiguous consortia, resulting in higher unnecessary costs to the taxpayer. The main contribution of this article is to propose a model of territorial partitioning that does not depend on extra restrictions to maintain contiguous clusters. This was possible due to the use of the Haversine distance between each municipality as the cost variable in a p-Medians Problem (PMP) model. The data for the municipalities and MSW production were obtained from the Brazilian Institute of Geography and Statistics (IBGE) and from the State Secretariat for the Environment and Water Resources (SEMA-PR) databases. The road distance between each municipality (shortest route) was consulted using the Google Distance Matrix API. Two simulations were conducted to determine the best configuration of this waste distribution network. The first simulation did not consider already existing landfills. In other words, an ideal situation was proposed that was impractical because there are already operational landfills in the state. It would be a feasible alternative if the objective was to implement a new network. This model reduced transport costs by approximately 49% compared with the current system. Moreover, it would cost 4.4% less to construct than the existing one. The second simulation considered the state's operational landfills, altering only the customer base and respective capacities. It was concluded that it would be necessary to add 25 new landfills to fully meet the requirements of the state. In this more realistic simulation, transport costs were reduced by around 80% and the cost of its construction would be only approximately 6% higher than the current solution. Policy makers and urban planners will be able to use this optimization model in decision making regarding the improvement of MSW management systems and reverse logistics, allowing for improvements for serving citizens and reducing the environmental impact.