Global Optimization by Natural Design

Some natural processes and principles have stimulated researchers to develop algorithms that imitate concepts of nature and are, therefore, summarized under the name natural computation (Kateman [1990] Lucasius [1994]). The most prominent methods are  

The initial data are binary coded in form of a bit sequence (bit string4). Start values of the variables x, x2. xm could be, e.g., 011001011,100101100,. ..,010010101. This initial population is undertaken an evolution process such as schematically represented in Fig. 5.8. 

For the selection and reproduction step the idea of elitism plays a role in so far as individuals of high quality should not become extinct. On the other hand, a larger number of elitists produces untimely a homogenisation of the population. 

The advantage of Genetic Algorithms, in contrast to the traditional optimization methods, is the fact that a large number of variables can be included into the process. Also in the presence of local optima, GA can find rapidly the global optimum. 

4 Also called chromosomea bit in this chromosome is then called gen . 

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