Multi-Objective Optimization Using

1. Auflage 2009
ISBN: 978-0-470-74361-4
Verlag: John Wiley & Sons

Buch, Englisch, 544 Seiten, Format (B × H): 170 mm x 244 mm, Gewicht: 927 g

The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists.

Evolutionary algorithms are very powerful techniques used to find solutions to real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run.
- Comrephensive coverage of this growing area of research.
- Carefully introduces each algorithm with examples and in-depth discussion.
- Includes many applications to real-world problems, including engineering design and scheduling.
- Includes discussion of advanced topics and future research.
- Accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms

Provides an extensive discussion on the principles of multi-objective optimization and on a number of classical approaches.

This integrated presentation of theory, algorithms and examples will benefit those working in the areas of optimization, optimal design and evolutionary computing.

Autoren/Hrsg.

Deb, Kalyanmoy

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik

Inhaltsverzeichnis

Foreword.

Preface.

Prologue.

Multi-Objective Optimization.

Classical Methods.

Evolutionary Algorithms.

Non-Elitist Multi-Objective Evolutionary Algorithms.

Elitist Multi-Objective Evolutionary Algorithms.

Constrained Multi-Objective Evolutionary Algorithms.

Salient Issues of Multi-Objective Evolutionary Algorithms.

Applications of Multi-Objective Evolutionary Algorithms.

Epilogue.

References.

Index.

Über Autor(innen)

Kalyanmoy Deb is an Indian computer scientist. Since 2013, Deb has held the Herman E. & Ruth J. Koenig Endowed Chair in the Department of Electrical and Computing Engineering at Michigan State University, which was established in 2001.