A Java-based Parallel Genetic Algorithm for the Land Use Planning Problem

In this work, the application of genetic algorithms to the elaboration of land use plans is studied. These plans follow the national legal rules and experts' considerations. Two optimization criteria are applied: aptitude and compactness. As the number of affected plots can be large and, consequently, the execution time of the algorithm can be potentially high, the work is focused on the implementation and analysis of different parallel paradigms: multi-core parallelism, cluster parallelism and the combination of both.

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