Genetic Algorithms in the Real World' seeks to bring together expert contributions on the theory and implementation of genetic algorithms: adaptive heuristic search algorithms inspired by the processes of natural selection, which search for optimized solutions through selection, recombination and mutation. Today, these algorithms are widely used in fields including finance, robotics, social sciences and business. Over more than a dozen chapters, 'Genetic Algorithms in the Real World' offers the reader high-quality, thoroughly researched examples detailing the practical uses of genetic algorithms in such applications as robot kinematics, handwriting recognition, artificial trading systems, biomechanics, fast electromagnetic synthesis, design of fractal frequency scheduling, machine scheduling, speech synthesizers and timetabling. The book covers new and established approaches including hybrid and multi-objective genetic algorithms and surrogate-based optimization. The case study based approach taken by the contributors ensures that this book will inspire and inform engineers and scientists seeking optimization solutions in numerous real-world situations.
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