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This book highlights recent research on metaheuristics for biomedical engineering, addressing both theoretical and applications aspects. Given the multidisciplinary nature of bio-medical image analysis, it has now become one of the most central topics in computer science, computer engineering and electrical and electronic engineering, and attracted the interest of many researchers. To deal with these problems, many traditional and recent methods, algorithms and techniques have been proposed. Among them, metaheuristics is the most common choice. This book provides essential content for senior and young researchers interested in methodologies for implementing metaheuristics to help solve biomedical engineering problems.

Engineering. --- Artificial intelligence. --- Computational intelligence. --- Biomedical engineering. --- Computational Intelligence. --- Biomedical Engineering. --- Artificial Intelligence (incl. Robotics). --- Clinical engineering --- Medical engineering --- Intelligence, Computational --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Construction --- Bioengineering --- Biophysics --- Engineering --- Medicine --- Artificial intelligence --- Soft computing --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Industrial arts --- Technology --- Biomedical Engineering and Bioengineering. --- Artificial Intelligence. --- Heuristic algorithms. --- Mathematical optimization.

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This book is an updated effort in summarizing the trending topics and new hot research lines in solving dynamic problems using metaheuristics. An analysis of the present state in solving complex problems quickly draws a clear picture: problems that change in time, having noise and uncertainties in their definition are becoming very important. The tools to face these problems are still to be built, since existing techniques are either slow or inefficient in tracking the many global optima that those problems are presenting to the solver technique. Thus, this book is devoted to include several of the most important advances in solving dynamic problems. Metaheuristics are the more popular tools to this end, and then we can find in the book how to best use genetic algorithms, particle swarm, ant colonies, immune systems, variable neighborhood search, and many other bioinspired techniques. Also, neural network solutions are considered in this book. Both, theory and practice have been addressed in the chapters of the book. Mathematical background and methodological tools in solving this new class of problems and applications are included. From the applications point of view, not just academic benchmarks are dealt with, but also real world applications in logistics and bioinformatics are discussed here. The book then covers theory and practice, as well as discrete versus continuous dynamic optimization, in the aim of creating a fresh and comprehensive volume. This book is targeted to either beginners and experienced practitioners in dynamic  optimization, since we took care of devising the chapters in a way that a wide audience could profit from its contents. We hope to offer a single source for up-to-date information in dynamic optimization, an inspiring and attractive new research domain that appeared in these last years and is here to stay.

Engineering & Applied Sciences --- Computer Science --- Combinatorial optimization. --- Computer algorithms. --- Computational intelligence. --- Intelligence, Computational --- Optimization, Combinatorial --- Engineering. --- Artificial intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Artificial intelligence --- Soft computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Algorithms --- Combinatorial analysis --- Mathematical optimization --- Artificial Intelligence.