Genetic Algorithms. Concepts and Designs



A new book from the University of Cantabria’s library: Genetic Algorithms. Concepts and Designs. By Kim F. Man, K. S. Tang, S. Kwong. Contributor S. Kwong. Published 1999. Springer. 344 pages. ISBN:1852330724.

It is a Springer book in a series titled: Advanced textbooks in control and signal processing.

This is the text in the back cover:

The practical application of Genetic Algorithms to the solution of engineering problems, is rapidly becoming an established approach in the fields of control and signal processing. This book provides comprehensive coverage of the techniques involved, describing the intrinsic characteristics, advantages and constraints of genetic algorithms, as well as discussing genetic operations such as crossover, mutation and reinsertion. In addition, the principle of multiobjective optimization and computing parallelism are discussed. These features are fully illustrated by real-world applications. Also described is a newly proposed and unique hierarchical genetic algorithm designed to address the problems in determining system topology.

Genetic Algorithms provides comprehensive coverage of the techniques involved, describing the intrinsic characteristics, advantages and constraints of genetic algorithms, as well as discussing genetic operations such as crossover, mutation and reinsertion. In addition, the principle of multiobjective optimization and computing parallelism are discussed. The use of genetic algorithms in many areas of interest in control and signal processing is detailed; among the areas of application are:

• filtering;

• H-infinity control;

• speech recognition;

• production planning and scheduling;

• computational intelligence; and

• communication systems.

Also described is an original hierarchical genetic algorithm designed to address the problems in determining system topology.

The authors provide “A Game of Genetic Creatures“, a fundamental study for GA based on computer-generated insects to demonstrate some of the ideas developed in the text. Professor Kim-Fung Man has got also a pretty flash presentation about Genetic Algorithms.

Contents:

– Introduction, Background and Biological Inspiration.
– Modifications to Genetic Algorithms.
– Intrinsic Characteristics.
– Hierarchical Genetic Algorithm.
– Genetic Algorithms in Filtering.
– Genetic Algorithms in H-infinity Control.
– Hierarchical Genetic Algorithms in Computational Intelligence.
– Genetic Algorithms in Speech Recognition Systems.
– Genetic Algorithms in Production Planning and Scheduling Problems.
– Genetic Algorithms in Communication Systems.
– Appendices: Least Mean Square Time Delay Estimation; Constrained LMS Algorithm; Linear Distributed Random Generator; Multiplication Algorithm; Digital IIR Filter Designs; Development Tools.

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