Multi-Objective Optimization Methods Based on Artificial Neural Networks

CARCANGIU, SARA;FANNI, ALESSANDRA;MONTISCI, AUGUSTO
2011-01-01

Abstract

Search algorithms aim to find solutions or objects with specified properties and constraints in a large solution search space or among a collection of objects. A solution can be a set of value assignments to variables that will satisfy the constraints or a sub-structure of a given discrete structure. In addition, there are search algorithms, mostly probabilistic, that are designed for the prospective quantum computer. This book demonstrates the wide applicability of search algorithms for the purpose of developing useful and practical solutions to problems that arise in a variety of problem domains. Although it is targeted to a wide group of readers: researchers, graduate students, and practitioners, it does not offer an exhaustive coverage of search algorithms and applications. The chapters are organized into three parts: Population-based and quantum search algorithms, Search algorithms for image and video processing, and Search algorithms for engineering applications.
2011
Search Algorithms and Applications
Nashat Mansour
Nashat Mansour
313
334
22
INTECH open
RIJEKA
978-953-307-156-5
http://www.intechopen.com/articles/show/title/multi-objective-optimization-methods-based-on-artificial-neural-networks
Esperti anonimi
info:eu-repo/semantics/bookPart
2.1 Contributo in volume (Capitolo o Saggio)
Carcangiu, Sara; Fanni, Alessandra; Montisci, Augusto
2 Contributo in Volume::2.1 Contributo in volume (Capitolo o Saggio)
3
268
none
Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Questionnaire and social

Share on:
Impostazioni cookie