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Books > Science & Mathematics > Mathematics > Algebra
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Search and Optimization by Metaheuristics - Techniques and Algorithms Inspired by Nature (Paperback, Softcover reprint of the original 1st ed. 2016)
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Search and Optimization by Metaheuristics - Techniques and Algorithms Inspired by Nature (Paperback, Softcover reprint of the original 1st ed. 2016)
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This textbook provides a comprehensive introduction to
nature-inspired metaheuristic methods for search and optimization,
including the latest trends in evolutionary algorithms and other
forms of natural computing. Over 100 different types of these
methods are discussed in detail. The authors emphasize non-standard
optimization problems and utilize a natural approach to the topic,
moving from basic notions to more complex ones. An introductory
chapter covers the necessary biological and mathematical
backgrounds for understanding the main material. Subsequent
chapters then explore almost all of the major metaheuristics for
search and optimization created based on natural phenomena,
including simulated annealing, recurrent neural networks, genetic
algorithms and genetic programming, differential evolution, memetic
algorithms, particle swarm optimization, artificial immune systems,
ant colony optimization, tabu search and scatter search, bee and
bacteria foraging algorithms, harmony search, biomolecular
computing, quantum computing, and many others. General topics on
dynamic, multimodal, constrained, and multiobjective optimizations
are also described. Each chapter includes detailed flowcharts that
illustrate specific algorithms and exercises that reinforce
important topics. Introduced in the appendix are some benchmarks
for the evaluation of metaheuristics. Search and Optimization by
Metaheuristics is intended primarily as a textbook for graduate and
advanced undergraduate students specializing in engineering and
computer science. It will also serve as a valuable resource for
scientists and researchers working in these areas, as well as those
who are interested in search and optimization methods.
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