Engineering optimization using simple evolutionary algorithm

This paper presents a simple (1 + λ) 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.