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Ouvrages Année : 2017

Evolutionary algorithms

Résumé

Evolutionary algorithms are bio inspired algorithms based on the Darwin's theory. They are expected to provide non-optimal but good quality solutions to problems whose resolution is impracticable by exact methods. 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 gives 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. Chapter 6 describes different approaches of genetic programming able to evolve computer programs in the context of machine learning
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Dates et versions

hal-01677858 , version 1 (08-01-2018)

Identifiants

  • HAL Id : hal-01677858 , version 1

Citer

Alain Petrowski, Sana Ben Hamida. Evolutionary algorithms. ISTE Ltd, John Wiley & sons Volume 9, pp.236, 2017, Computer engineering series, metaheuristics set, Computer engineering series, metaheuristics set, 978-1-84821-804-8. ⟨hal-01677858⟩
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