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Describes several generic algorithmic concepts that can be used in various kinds of GA or with evolutionary optimization techniques. This title provides a better understanding of the basic workflow of GAs and GP, encouraging readers to establish new bionic, problem-independent theoretical concepts.

This book demonstrates the versatility of the increasingly multi-disciplinary field of mathematical modelling and will be an insightful book of interest to specialists, teachers and students in areas from mechanics to social science

This book describes several generic algorithmic concepts that can be used in any kind of GA or with evolutionary optimization techniques. It provides a better understanding of the basic workflow of GAs and GP, encouraging readers to establish new bionic, problem-independent theoretical concepts. By comparing the results of standard GA and GP implementation with several algorithmic extensions, the authors show how to substantially increase achievable solution quality. They also describe structure identification using HeuristicLab as a platform for algorithm development. Software, dynamical presentations of representative test runs, and more are available on a supplementary website.

Demonstrating how to use personal computers for modeling and simulation, this practical tutorial discusses how to effectively simulate dynamical systems, such as aerospace vehicles, power plants, chemical processes, control systems, and physiological systems. This edition introduces a new vectorizing compiler for fast vector operations and param