A multi-objective genetic algorithm based approach for location of grain silos in Paraná State of Brazil

Abstract The production of soybean and corn has increased steadily in Brazil, with the Parana State being the second largest producer of these grains. The increased production has now necessitated the storing facility also to be increased. Accordingly, partitioning the storage facility is a proposal to aggregate the municipalities of Parana into regions for effective transportation of the grains. Motivated by the requirement, the present work aims to organize the storage regions by aggregating the municipalities as a multi-objective graph (territory) partitioning problem with the municipalities being the nodes and roads linking them as the edges of the graph. In order to find the effective number of new silos to be constructed and their region-wise locations, maximization of the homogeneity of storage deficit and minimization of the inter-region product transportation cost from production sources to storage points are considered as two objective functions for the problem. A multi-objective genetic algorithm based results, presented here, should have a strong impact on the grain storage system management in Parana. Moreover, the proposed methodology might act as a useful grain storage management decision aiding tool in other territories.