Advances in Evolutionary Algorithms Research

Gregor Papa

ISBN 10: 1634638492 / ISBN 13: 9781634638494

Published by Nova Science Publishers Inc Jun 2015, 2015

About this Item

Neuware - The field of evolutionary algorithms produces various theoretical approaches that help search for global optima within complex environments. These environments are often highly multidimensional, non-linear, noisy, and with many constraints. Not only one, but frequently several, even conflicting, objectives need to be met while searching for the optimal solutions. This book presents advances in the research and applications of evolutionary algorithms. There is a rich history of theoretical research and practical solutions in this field. Namely, evolutionary algorithms, with their intrinsic parallelism, have proved to be successful in a variety of problem domains in science, engineering and business. According to the no-free lunch theorem for optimisation no super algorithm exists for all optimisation problems. Therefore, the advances in this research field are also devoted to the identification of combination of problem classes and effective optimisation methods, as well as the innovative and hybrid implementations of the algorithms. This book consists of seven chapters covering the survey and theory on multimodal, multi-memetic and multi-objective properties and algorithm performance. Furthermore, the algorithms are applied to real-world mechanical, biological, and chemical problems, as well as to theoretical benchmarks.

Seller Inventory # 9781634638494

Bibliographic Details

• Title: Advances in Evolutionary Algorithms Research
• Publisher: Nova Science Publishers Inc Jun 2015
• Publication Date: 2015
• Language: English
• ISBN 10: 1634638492
• ISBN 13: 9781634638494
• Binding: Buch
• Condition: Neu
• Dimensions: 264W x 214H x 15D millimeters 264 millimeters width by 214 millimeters height by 15 millimeters depth
• Weight: 474 grams

About this title

Synopsis

The field of evolutionary algorithms produces various theoretical approaches that help search for global optima within complex environments. These environments are often highly multidimensional, non-linear, noisy, and with many constraints. Not only one, but frequently several, even conflicting, objectives need to be met while searching for the optimal solutions. This book presents advances in the research and applications of evolutionary algorithms. There is a rich history of theoretical research and practical solutions in this field. Namely, evolutionary algorithms, with their intrinsic parallelism, have proved to be successful in a variety of problem domains in science, engineering and business. According to the no-free lunch theorem for optimisation no super algorithm exists for all optimisation problems. Therefore, the advances in this research field are also devoted to the identification of combination of problem classes and effective optimisation methods, as well as the innovative and hybrid implementations of the algorithms. This book consists of seven chapters covering the survey and theory on multimodal, multi-memetic and multi-objective properties and algorithm performance. Furthermore, the algorithms are applied to real-world mechanical, biological, and chemical problems, as well as to theoretical benchmarks.