Engineering optimization using simple evolutionary algorithm

This paper presents a simple (1 + /spl lambda/) evolution strategy and three simple selection criteria to solve engineering optimization problems and indicates that the proposed technique is highly competitive in terms of quality, robustness and computational cost.

Abstract

This paper presents a simple (1 + /spl lambda/) evolution strategy and three simple selection criteria to solve engineering optimization problems. This approach avoids the use of a penalty function to deal with constraints. Its main advantage is that it does not require the definition of extra parameters, other than those used by the evolution strategy. A self-adaptation mechanism allows the algorithm to maintain diversity during the process in order to reach competitive solutions at a low computational cost. The approach was tested in four well-known engineering design problems and compared against several penalty-function-based approaches and other state-of-the-art technique. The results obtained indicate that the proposed technique is highly competitive in terms of quality, robustness and computational cost.