A novel genetic algorithmic approach for computing real roots of a nonlinear equation

Abstract

Novel Pre-processing and Post-processing methodologies are designed to enhance the performance of the classical Genetic Algorithms (GA) approach so as to obtain efficient interval estimates in finding the real roots of a given nonlinear equation. The Pre-processing methodology suggests a mechanism that adaptively fixes the parameter-‘length of chromosome’ in GA. The proposed methodologies have been implemented and demonstrated through a set of benchmark functions to illustrate the effectiveness.