This book presents a unified view of evolutionary algorithms: the exciting new probabilistic search tools inspired by biological models that have immense potential as practical problem-solvers in a wide variety of settings, academic, commercial, and industrial. In this work, the author compares the three most prominent representatives of evolutionary algorithms: genetic algorithms, evolution strategies, and evolutionary programming. The algorithms are presented within a unified framework, thereby clarifying the similarities and differences of these methods. The author also presents new...

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.

This volume, which includes the author's own software package, tracks the development of evolutionary computation since 1990, with detailed evaluations of key approaches, pseudocode representations of each algorithm, and industry-applicable BBOB benchmarking.

This volume, which includes the author's own software package, tracks the development of evolutionary computation since 1990, with detailed evaluations of key approaches, pseudocode representations of each algorithm, and industry-applicable BBOB benchmarking.