by Eisuke Kita
Publisher: InTech 2011
Number of pages: 584
Evolutionary algorithms are successively applied to wide optimization problems in the engineering, marketing, operations research, and social science, such as include scheduling, genetics, material selection, structural design and so on. Apart from mathematical optimization problems, evolutionary algorithms have also been used as an experimental framework within biological evolution and natural selection in the field of artificial life.
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by Witold Kosinski - InTech
With the recent trends towards massive data sets and significant computational power, evolutionary computation is becoming much more relevant to practice. The book presents recent improvements, ideas and concepts in a part of a huge EA field.
by Thomas Weise
The book on global optimization algorithms - methods to find optimal solutions for given problems. It focuses on evolutionary algorithms, genetic algorithms, genetic programming, learning classifier systems, evolution strategy, etc.
by Adam Marczyk - The TalkOrigins Archive
Creationists argue that evolutionary processes cannot create new information, or that evolution has no practical benefits. This article disproves those claims by describing the explosive growth and widespread applications of genetic algorithms.
by Sebastian Ventura (ed.) - InTech
Genetic programming (GP) is a branch of Evolutionary Computing that aims the automatic discovery of programs to solve a given problem. Since its appearance, in the earliest nineties, GP has become one of the most promising paradigms ...