TY  - BOOK
AU  - P�etrowski,Alain
AU  - Ben-Hamida,Sana
TI  - Evolutionary algorithms
T2  - Metaheuristics set
SN  - 9781119136415
AV  - QA402.5 
U1  - 519.3 23
PY  - 2017///
CY  - London
PB  - ISTE
KW  - Genetic algorithms
KW  - Algorithmes g�en�etiques
KW  - MATHEMATICS
KW  - Applied
KW  - bisacsh
KW  - Probability & Statistics
KW  - General
KW  - fast
N1  - Includes bibliographical references and index; 1. Evolutionary Algorithms; 2. Continuous Optimization; 3. Constrained Continuous Evolutionary Optimization; 4. Combinatorial Optimization; 5. Multi-objective Optimization; 6. Genetic Programming for Machine Learning
N2  - Evolutionary algorithms are bio-inspired algorithms based on Darwin's 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
UR  - https://onlinelibrary.wiley.com/doi/book/10.1002/9781119136378
ER  -