{"product_id":"multi-objective-optimization-in-computational-intelligence-theory-and-practice-9781599044989","title":"Multi-Objective Optimization in Computational Intelligence: Theory and Practice","description":"\u003cp\u003e • Author(s): Lam Thu Bui | Sameer Alam\u003cbr\u003e • Publisher: Information Science Reference\u003cbr\u003e • Publisher Imprint: Information Science Reference\u003cbr\u003e • BISAC: Probability \u0026amp; Statistics - General\u003c\/p\u003e\u003cp\u003eMulti-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.\u003c\/p\u003e","brand":"Information Science Reference","offers":[{"title":"Hardcover","offer_id":47611554922647,"sku":"9781599044989","price":18395.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9781599044989.webp?v=1775071436","url":"https:\/\/atlanticbooks.com\/products\/multi-objective-optimization-in-computational-intelligence-theory-and-practice-9781599044989","provider":"Atlantic Books","version":"1.0","type":"link"}