| 书目名称 | Search and Optimization by Metaheuristics | | 副标题 | Techniques and Algor | | 编辑 | Ke-Lin Du,M. N. S. Swamy | | 视频video | | | 概述 | Offers a comprehensive and state-of-the-art introduction to nature-inspired metaheuristics.Includes detailed, implementable algorithmic flowcharts for the most popular algorithms.Discusses over 100 di | | 图书封面 |  | | 描述 | 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 det | | 出版日期 | Textbook 2016 | | 关键词 | Metaheuristics; Evolutionary Computation; Natural Computing; Swarm Intelligence; Optimization | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-41192-7 | | isbn_softcover | 978-3-319-82290-7 | | isbn_ebook | 978-3-319-41192-7 | | copyright | Springer International Publishing Switzerland 2016 |
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发表于 2025-3-21 17:26:27
