{"product_id":"9780470937419","title":"Evolutionary Optimization Algorithms","description":"\u003ch1\u003eEvolutionary Optimization Algorithms\u003c\/h1\u003e\u003ch3\u003eDan Simon\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eMathematics \/ Discrete Mathematics\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp\u003e\u003cb\u003eA clear and lucid bottom-up approach to the basic principles of evolutionary algorithms\u003c\/b\u003e \t \u003c\/p\u003e\n\u003cp\u003eEvolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies. \u003c\/p\u003e\n\u003cp\u003eThis book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others. \u003c\/p\u003e\n\u003cp\u003e\u003ci\u003eEvolutionary Optimization Algorithms:\u003c\/i\u003e \u003c\/p\u003e\n\u003cul\u003e \u003cli\u003eProvides a straightforward, bottom-up approach that assists the reader in obtaining a clear—but theoretically rigorous—understanding of evolutionary algorithms, with an emphasis on implementation\u003c\/li\u003e \u003cli\u003eGives a careful treatment of recently developed EAs—including opposition-based learning, artificial fish swarms, bacterial foraging, and many others— and discusses their similarities and differences from more well-established EAs\u003c\/li\u003e \u003cli\u003eIncludes chapter-end problems plus a solutions manual available online for instructors\u003c\/li\u003e \u003cli\u003eOffers simple examples that provide the reader with an intuitive understanding of the theory\u003c\/li\u003e \u003cli\u003eFeatures source code for the examples available on the author's website\u003c\/li\u003e \u003cli\u003eProvides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eEvolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e  \u003cp\u003e\u003cb\u003e\u003csmall\u003eDAN SIMON \u003c\/small\u003e\u003c\/b\u003eis a Professor at Cleveland State University in the Department of Electrical and Computer Engineering. His teaching and research interests include control theory, computer intelligence, embedded systems, technical writing, and related subjects. He is the author of the book Optimal State Estimation (Wiley). \u003c\/p\u003e\n\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e29 April 2013\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eWiley\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eWiley\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9780470937419\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e784\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWeight (oz): \u003c\/td\u003e\n\u003ctd\u003e43.2\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":44310854205580,"sku":"9780470937419","price":132.26,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9780470937419.jpg?v=1780204300","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9780470937419","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}