Uso de algoritmos evolucionários na calibração de modelos hidrológicos e na operação de sistemas de reservatórios

Abstract

Experience suggests that any single-objective search, no matter how carefully chosen, is not able to identify a solution capable of satisfactorily model a phenomenum of interest. Use of a multiobjective approach can yet be justified by the nature of real world problems, which in general involve multiobjectives, most of the time conflicting objectives. An approach very often used in multicriteria optimization is the concept of Pareto dominance, which allows us to compare different solutions by using different objectives and to explore different characteristics of the observed data. This dissertation employs evolutionary algorithms inspired on honey-bee mating for single (Honey-Bee Mating Optimization - HBMO) e multiobjectives (Multiobjective Honey-Bee Mating Optimization - MOHBMO) in the minimization of test functions and calibration of watershed models. The singleobjective version is the one introduced by Haddad et al. (2006), while its multiobjective version is proposed by the present work. As reference of their performance, the following algorithms were used: PSO (Particle Swarm Optimization), and its multiobjective version MOPSO (Multiobjective Particle Swarm), SCEM (Shuffled Complex Evolucion Metropolis) and its multiobjective version MOSCEM (Multiobjective Shuffled Complex Evolucion Metropolis). Well known theoretical functions were used to test the proposed algorithms. Real world applications on hydrologic model calibration employing HYMOD and SMAP models, with daily time steps, were carried out for 15 streamflow gauge stations located in the states of Ceará e Piauí. Besides, an optimization study for the operation of the reservoir system that supplies water for the Metropolitan Region of Fortaleza was also executed.