Overview

This book is a continuation of the Genetic Algorithms Reference series, the first volume of which was devoted to crossover operators. The current, second volume presents mutation operators destined to solve numerical optimization problems. The layout of this book follows the layout of the former volume, however, the simple division into operators dedicated to solving problems coded with binary and real numbers was insufficient this time. Research work on the mutation operator does not lead only to development of its new, frequently dedicated form. One of the main questions asked in connection with this operator is about the probability of its application and about the scale of perturbation introduced by this operator. Therefore, three out of seven chapters of this book are devoted to this issue. Moreover, following the readers' opinions as well as suggestions of the reviewer of the first volume, I decided to add a chapter which is an introduction to the genetic algorithms theory. It is directed at everyone who starts their adventure involving genetic algorithms with this book series. Eventually the layout of this book is as follows.The first chapter provides a general introduction to the genetic algorithms theory. The following three chapters present suggestions, formulas and methods applied in determining values of parameters controlling the mutation process. Here I have applied the most popular division into: static and deterministic approach, dynamic adaptive approach and self-adaptive approach. Two of the last chapters present mutation operators developed with problems coded with binary and real numbers in mind. You can find more information on my Web page (www.tomaszgwiazda.pl).

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