IMPROVEMENT IN A GENETIC ALGORITHM FOR OPTIMIZATION OF RUNOFF-EROSION MODELS

Abstract

In order to provide a robust tool to be used in runoff-erosion modeling, the present paper introduces new evolution steps in the SCE-UA genetic algorithm, which is based in the simplextheory. The new evolution steps were conceived in order to improve the efficiency of such an algorithm. Thus, they will theoretically expand the simplex in a direction of more favorable conditions, or contract it if a move is taken in a direction of less favorable conditions. Hence, these new evolution steps enable the simplex both to accelerate along a successful track of improvement and to home in on the optimum conditions. Therefore, it will usually reach the optimum region quicker than the previous version and pinpoint the optimum levels more closely. The new proposed algorithm is tested with special mathematical functions, as well as in the optimization of the erosion parameters presented in a physically-based runoff-erosion model. On the basis of these simulation results, the mean erosion parameter valuesare given, which agree with previous values reported to the same area. Thus, the new algorithm can be considered as a promising tool to optimize physically-based models as well as other kinds of models.