VDI 6224 Blatt 1:2012-06 (R2017)

Bionic methods for optimization have already often been used successfully in industrial sectors, but they still have a great potential for further application. Evolutionary strategies are robust algorithms for optimization. Designed after the the biological evolution they are suitable for the optimization of various processes and products, and can be used successfully in almost every company. Evolutionary algorithms use the principles of variation (mutation and recombination) and selection, executed iteratively in an evolutionary loop, to evolve new solutions with the objective of improving and optimizing the system. In this process, variation supplies the genetic material (diversity) and selection pushes evolution in the (desired) direction. The Darwinian evolution paradigm can be implemented algorithmically in various ways. These implementations differ in the degree to which they model the biological machinery, among other differences. Using this guideline optimization problems can be solved for which there is no known standard solutions or algorithms, for which the standard solutions or algorithms do not yield the desired success or whose solution using conventional methods appears to be too expensive.