In previous works we have shown that applying genetic algorithms to solve the Root Identification Problem is feasible and effective. The behavior of evolutive algorithms is characterized by a set of parameters that have an
effect on the algorithms’ performance. In this paper we report on an empirical statistical study conducted to establish the influence of the driving
parameters in the Population Based Incremental Learning (PBIL) algorithm when applied to solve the Root Identification Problem. We also identify
ranges for the parameters values that optimize the algorithm performance.Postprint (author’s final draft
