Evolutionary Algorithms for Solving Multi-Objective Problems
(Sprache: Englisch)
This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. It provides links to a complete set of teaching tutorials, exercises and solutions.
Voraussichtlich lieferbar in 3 Tag(en)
versandkostenfrei
Buch (Kartoniert)
Fr. 100.50
inkl. MwSt.
- Kreditkarte, Paypal, Rechnungskauf
- 30 Tage Widerrufsrecht
Produktdetails
Produktinformationen zu „Evolutionary Algorithms for Solving Multi-Objective Problems “
This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. It provides links to a complete set of teaching tutorials, exercises and solutions.
Klappentext zu „Evolutionary Algorithms for Solving Multi-Objective Problems “
Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems. Evolutionary algorithms are one such generic stochastic approach that has proven to be successful and widely applicable in solving both single-objective and multi-objective problems. 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 variety of practical problems, including test suites with associated performance based on a variety of appropriate metrics, as well as serial and parallel algorithm implementations.
Inhaltsverzeichnis zu „Evolutionary Algorithms for Solving Multi-Objective Problems “
- Basic Concepts- MOP Evolutionary Algorithm Approaches
- MOEA Local Search and Coevolution
- MOEA Test Suites
- MOEA Testing and Analysis
- MOEA Theory and Issues
- Applications
- MOEA Parallelization
- Multi-Criteria Decision Making
- Alternative Metaheuristics
Bibliographische Angaben
- Autoren: Carlos Coello Coello , Gary B. Lamont , David A. van Veldhuizen
- 2014, 2. Aufl., XXI, 800 Seiten, Masse: 15,4 x 23,4 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 1489994602
- ISBN-13: 9781489994608
Sprache:
Englisch
Kommentar zu "Evolutionary Algorithms for Solving Multi-Objective Problems"
0 Gebrauchte Artikel zu „Evolutionary Algorithms for Solving Multi-Objective Problems“
| Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
|---|
Schreiben Sie einen Kommentar zu "Evolutionary Algorithms for Solving Multi-Objective Problems".
Kommentar verfassen