{"product_id":"evolutionary-algorithms-computer-engineering-metaheuristics-9-1848218044","title":"Evolutionary Algorithms (Computer Engineering: Metaheuristics, 9)","description":"\u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 1848218044\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Petrowski, Alain\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e New\u003c\/p\u003e\u003cp\u003eEvolutionary algorithms are bio-inspired algorithms based on Darwins theory of evolution. They are expected to provide non-optimal but good quality solutions to problems whose resolution is impracticable by exact methods.In six chapters, this book presents the essential knowledge required to efficiently implement evolutionary algorithms.Chapter 1 describes a generic evolutionary algorithm as well as the basic operators that compose it. Chapter 2 is devoted to the solving of continuous optimization problems, without constraint. Three leading approaches are described and compared on a set of test functions. Chapter 3 considers continuous optimization problems with constraints. Various approaches suitable for evolutionary methods are presented. Chapter 4 is related to combinatorial optimization. It provides a catalog of variation operators to deal with order-based problems. Chapter 5 introduces the basic notions required to understand the issue of multi-objective optimization and a variety of approaches for its application. Finally, Chapter 6 describes different approaches of genetic programming able to evolve computer programs in the context of machine learning.\u003c\/p\u003e","brand":"Mia Karts","offers":[{"title":"Default Title","offer_id":68137112109344,"sku":"NEW1848218044","price":191.92,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/618NvKlil5S.jpg?v=1793817167","url":"https:\/\/miakarts.com\/products\/evolutionary-algorithms-computer-engineering-metaheuristics-9-1848218044","provider":"Miakarts Books","version":"1.0","type":"link"}