Population Genetics and Evolutionary Computation: Theoretical and Practical Aspects - Softcover

Affenzeller, Michael

 
9783854878230: Population Genetics and Evolutionary Computation: Theoretical and Practical Aspects

Inhaltsangabe

Due to their successful implementation in difficult and hard problems in various fields of theoretical and practical applications, the importance and application potential of capable heuristics has been increasing continuously throughout the last decades. Particularly Evolutionary Computation concepts are known to be able to achieve robust and high-quality solutions to difficult problems. Thanks to the rapidly increasing computational power available in the last few years, these methods capture more and more new fields of application including highly relevant fields like logistics, production planning, bio- and chemoinformatics, or data mining issues.

Even if the natural evolution process represents the role model for Evolutionary Algorithms, the technical realization in the different fields of Evolutionary Computation is highly simplified.

This book considers recent results of population genetics in order to present generic extensions to the general concept of a Genetic Algorithm. Consequently a new model for self-adaptive selection pressure steering is presented (Offspring Selection), taking advantage of the interplay between directed genetic drift and migration, resulting in a new class of Genetic Algorithms. As a result generic extensions to the general concepts of Genetic Algorithms are introduced and empirically analyzed, which make genetic search more stable in terms of operators, and allows steering and scaling up of global solution quality to highest quality regions without using problem specific information or local searches. All these newly introduced methods are brought together generically in the so called SASEGASA algorithm.

Priv.-Doz. DI Dr. Michael Affenzeller, Jahrgang 1972, Studium der Technischen Mathematik an der Johannes Kepler Universität Linz, Doktorat der technischen Wissenschaften 2001, Habilitation in angewandter Systemtheorie 2004.

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