Population Dynamics of Genetic Algorithms

The theory of evolutionary algorithms has developed significantly in the last few years.A variety of techniques and perspectives have been brought to bear on the analysis and understanding of these algorithms. However, it is fair to say that we are still some way away from a coherent theory that explains and predicts behaviour, and can give guidance to applied practitioners. Theory has so far developed in a fragmented, piecemeal fashion, with different researchers applying their own perspectives, and using tools with which they are familiar. This is beginning to change, as the research community develops and individual insights become shared. Consequently, the work presented in this chapter is a somewhat biased selection of results. However, I hope that other researchers will appreciate this material, even if they would themselves have concentrated on a different approach. Readers who are interested in a survey of current theory are referred to the books

Genetic algorithms: principles and perspectives [15] and Theoretical aspects of evolutionary computation

[9].