Mohlo by se vám také líbit

Více informací o knize Archiving Strategies for Evolutionary Multi-objective Optimization Algorithms

• Parametry knihy
• Anotace
• Oblíbené z jiného soudku

Nákupem získáte 330 bodů

Anotace knihy

This book presents an overview of archiving strategies developed over the last years by the authors that deal with suitable approximations of the sets of optimal and nearly optimal solutions of multi-objective optimization problems by means of stochastic search algorithms. All presented archivers are analyzed with respect to the approximation qualities of the limit archives that they generate and the upper bounds of the archive sizes. The convergence analysis will be done using a very broad framework that involves all existing stochastic search algorithms and that will only use minimal assumptions on the process to generate new candidate solutions. All of the presented archivers can effortlessly be coupled with any set-based multi-objective search algorithm such as multi-objective evolutionary algorithms, and the resulting hybrid method takes over the convergence properties of the chosen archiver. This book hence targets at all algorithm designers and practitioners in the field of multi-objective optimization.

Parametry knihy

Zařazení knihy Knihy v angličtině Computing & information technology Computer science Artificial intelligence

• Plný název: Archiving Strategies for Evolutionary Multi-objective Optimization Algorithms
• Autor: Oliver Schütze, Carlos Hernández
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 234
• EAN: 9783030637750
• ID: 38503556
• Nakladatelství: Springer Nature Switzerland AG
• Hmotnost: 385 g
• Rozměry: 235 × 155 × 14 mm
• Datum vydání: 06. January 2022

Oblíbené z jiného soudku

---

---

---