Search methods in structural optimization - mixed-discrete variables and parallel computing

The basic concepts of two search methods in structural optimization, genetic algorithms and evolution strategies, are introduced. These methods require only information of function-values. Because of their simple search mechanisms, they are well suited for wide classes of optimization problems. The increasing availability of high-speed and parallel computing caused a renewed interest in these zero-order methods, in particular in Monte-Carlo techniques, genetic algorithms and evolution strategies, which are described herein.