
Innovative Computing Methods and their Applications to Engineering Problems
Springer (Publisher)
Published on 26. May 2011
Book
Hardback
VIII, 164 pages
978-3-642-20957-4 (ISBN)
Description
The design of most modern engineering systems entails the consideration of a good trade-off between the several targets requirements to be satisfied along the system life such as high reliability, low redundancy and low operational costs. These aspects are often in conflict with one another, hence a compromise solution has to be sought. Innovative computing techniques, such as genetic algorithms, swarm intelligence, differential evolution, multi-objective evolutionary optimization, just to name few, are of great help in founding effective and reliable solution for many engineering problems. Each chapter of this book attempts to using an innovative computing technique to elegantly solve a different engineering problem.
More details
Series
Edition
2011 ed.
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
VIII, 164 p.
Dimensions
Height: 23.5 cm
Width: 15.5 cm
Weight
930 gr
ISBN-13
978-3-642-20957-4 (9783642209574)
DOI
10.1007/978-3-642-20958-1
Schweitzer Classification
Other editions
Additional editions

Nadia Nedjah | Leandro Santos Coelho | Viviana Cocco Mariani
Innovative Computing Methods and their Applications to Engineering Problems
Book
07/2013
Springer
€106.99
Shipment within 7-9 days

Nadia Nedjah | Leandro Santos Coelho | Viviana Cocco Mariani
Innovative Computing Methods and their Applications to Engineering Problems
E-Book
05/2011
Springer
€96.29
Available for download
Persons
Content
1- A discrete differential evolution approach with local search for traveling salesman problems.- 2- Genetic Algorithm based Reliability Optimization in Interval Environment.- 3- PSO for Building Fuzzy Systems.- 4- Maintenance optimization of wind turbine systems based on intelligent prediction tools.- 5- Clonal selection algorithm applied to economic dispatch optimization of electrical energy.- 6- Dynamic Objectives Aggregation Methods in Multi-objective Evolutionary Optimization.- 7- Application Mapping for Efficient NoC-based Implementation using Evolutionary Multi-objective Optimization.- 8- Theory and Applications of Chaotic Optimization Methods.