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Evolutionary Computation 2

Advanced Algorithms and Operators

Evolutionary Computation 2: Advanced Algorithms and Operators expands upon the basic ideas underlying evolutionary algorithms. The focus is on fitness evaluation, constraint-handling techniques, population structures, advanced techniques in evolutionary computation, and the implementation of evolutionary algorithms. It is intended to be used by individual researchers and students in the expanding field of evolutionary computation.

Evolutionary Computation 2: Advanced Algorithms and Operators expands upon the basic ideas underlying evolutionary algorithms.

Handbook of Evolutionary Computation

Many scientists and engineers now use the paradigms of evolutionary computation (genetic algorithms, evolution strategies, evolutionary programming, genetic programming, classifier systems, and combinations or hybrids) to tackle problems that are either intractable or unrealistically time consuming to solve through traditional computational strategies. The Handbook of Evolutionary Computation addresses the need for a comprehensive source of reference in the maturing field of evolutionary computation. The handbook is available in a looseleaf print format and an online format.

The Handbook of Evolutionary Computation addresses the need for a comprehensive source of reference in the maturing field of evolutionary computation. The handbook is available in a looseleaf print format and an online format.

Evolutionary Computation 1

Basic Algorithms and Operators

The field of evolutionary computation is expanding dramatically, fueled by the vast investment that reflects the value of applying its techniques. Culling material from the Handbook of Evolutionary Computation, Evolutionary Computation 1: Basic Algorithms and Operators contains up-to-date information on algorithms and operators used in evolutionary computing. This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming. It is intended to be used by individual researchers, teachers, and students working and studying in this expanding field.

This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming.