Recent Advances In Evolutionary Multi Objective Optimization

Download Recent Advances In Evolutionary Multi Objective Optimization full books in PDF, epub, and Kindle. Read online free Recent Advances In Evolutionary Multi Objective Optimization ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Recent Advances in Evolutionary Multi-objective Optimization

Recent Advances in Evolutionary Multi-objective Optimization
Author :
Publisher : Springer
Total Pages : 187
Release :
ISBN-10 : 9783319429786
ISBN-13 : 3319429787
Rating : 4/5 (787 Downloads)

Book Synopsis Recent Advances in Evolutionary Multi-objective Optimization by : Slim Bechikh

Download or read book Recent Advances in Evolutionary Multi-objective Optimization written by Slim Bechikh and published by Springer. This book was released on 2016-08-09 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-and coming scientists towards exciting prospects at the forefront of computational intelligence, the authors have made an effort to ensure that the ideas conveyed herein are accessible to the widest audience. The book begins with a summary of the basic concepts in multi-objective optimization. This is followed by brief discussions on various algorithms that have been proposed over the years for solving such problems, ranging from classical (mathematical) approaches to sophisticated evolutionary ones that are capable of seamlessly tackling practical challenges such as non-convexity, multi-modality, the presence of multiple constraints, etc. Thereafter, some of the key emerging aspects that are likely to shape future research directions in the field are presented. These include: optimization in dynamic environments, multi-objective bilevel programming, handling high dimensionality under many objectives, and evolutionary multitasking. In addition to theory and methodology, this book describes several real-world applications from various domains, which will expose the readers to the versatility of evolutionary multi-objective optimization.


Recent Advances in Evolutionary Multi-objective Optimization Related Books

Recent Advances in Evolutionary Multi-objective Optimization
Language: en
Pages: 187
Authors: Slim Bechikh
Categories: Technology & Engineering
Type: BOOK - Published: 2016-08-09 - Publisher: Springer

DOWNLOAD EBOOK

This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-and coming scien
Evolutionary Multiobjective Optimization
Language: en
Pages: 313
Authors: Ajith Abraham
Categories: Computers
Type: BOOK - Published: 2005-09-05 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Evolutionary Multi-Objective Optimization is an expanding field of research. This book brings a collection of papers with some of the most recent advances in th
Multi-Objective Optimization using Evolutionary Algorithms
Language: en
Pages: 540
Authors: Kalyanmoy Deb
Categories: Mathematics
Type: BOOK - Published: 2001-07-05 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Optimierung mit mehreren Zielen, evolutionäre Algorithmen: Dieses Buch wendet sich vorrangig an Einsteiger, denn es werden kaum Vorkenntnisse vorausgesetzt. Ge
Applications of Multi-objective Evolutionary Algorithms
Language: en
Pages: 792
Authors: Carlos A. Coello Coello
Categories: Computers
Type: BOOK - Published: 2004 - Publisher: World Scientific

DOWNLOAD EBOOK

- Detailed MOEA applications discussed by international experts - State-of-the-art practical insights in tackling statistical optimization with MOEAs - A unique
Advances in Multi-Objective Nature Inspired Computing
Language: en
Pages: 204
Authors: Carlos Coello Coello
Categories: Mathematics
Type: BOOK - Published: 2010-02-04 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

The purpose of this book is to collect contributions that deal with the use of nature inspired metaheuristics for solving multi-objective combinatorial optimiza