A Comparison of Evolutionary Algorithms for Mechanical Design Components

Abstract

Two evolutionary algorithms - the genetic algorithm and the evolution strategy - are compared in respect of mechanical design problems. Mechanical design problems are real world problems, characterized by a number of inequality constraints, nonlinear equations, mixed discrete-continuous variables and the presence of interdependent discrete parameters whose values are taken from standardized tables. The selection, recombination and mutation operators, and the chosen constraint-handling method are presented for both the genetic algorithm and the evolution strategy. In order to find the best combination of operators for each algorithm which will solve mechanical design problems, a number of selection and recombination operators are compared in respect of these problems. A comparison of these two algorithms with regard to three mechanical design problems extends the results of comparisons presented in the literature for unimodal and multimodal test functions with continuous variables only, and without constraints.