Evolutionary Algorithms Alan Petrowski Sana Benhamida by Alan Petrowski, Sana Ben-hamida 9781848218048, 1848218044 instant download after payment.

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. - Chapter 6 describes different approaches of genetic programming able to evolve computer programs in the context of machine learning.