Evolutionary Algorithms

Evolutionary Algorithms

Author: Alain Petrowski

Publisher: John Wiley & Sons

ISBN: 9781848218048

Category: Computers

Page: 256

View: 877

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.
Evolutionary Algorithms
Language: en
Pages: 256
Authors: Alain Petrowski, Zbigniew Michalewicz, Sana Ben-Hamida
Categories: Computers
Type: BOOK - Published: 2017-04-24 - Publisher: John Wiley & Sons

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 Algorithms
Language: en
Pages: 293
Authors: Lawrence D. Davis, Kenneth De Jong, Michael D. Vose, L.Darrell Whitley
Categories: Computers
Type: BOOK - Published: 2012-10-23 - Publisher: Springer

This IMA Volume in Mathematics and its Applications EVOLUTIONARY ALGORITHMS is based on the proceedings of a workshop that was an integral part of the 1996-97 IMA program on "MATHEMATICS IN HIGH-PERFORMANCE COMPUTING." I thank Lawrence David Davis (Tica Associates), Kenneth De Jong (Computer Science, George Mason University), Michael D.
Evolutionary Algorithms for Solving Multi-Objective Problems
Language: en
Pages: 800
Authors: Carlos Coello Coello, Gary B. Lamont, David A. van Veldhuizen
Categories: Computers
Type: BOOK - Published: 2007-08-26 - Publisher: Springer Science & Business Media

This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a
Evolutionary Algorithms in Engineering Applications
Language: en
Pages: 555
Authors: Dipankar Dasgupta, Zbigniew Michalewicz
Categories: Computers
Type: BOOK - Published: 2013-06-29 - Publisher: Springer Science & Business Media

Evolutionary algorithms are general-purpose search procedures based on the mechanisms of natural selection and population genetics. They are appealing because they are simple, easy to interface, and easy to extend. This volume is concerned with applications of evolutionary algorithms and associated strategies in engineering. It will be useful for engineers,
Illustrating Evolutionary Computation with Mathematica
Language: en
Pages: 578
Authors: Christian Jacob
Categories: Computers
Type: BOOK - Published: 2001 - Publisher: Morgan Kaufmann

An essential capacity of intelligence is the ability to learn. An artificially intelligent system that could learn would not have to be programmed for every eventuality; it could adapt to its changing environment and conditions just as biological systems do. Illustrating Evolutionary Computation with Mathematica introduces evolutionary computation to the