Multi-objective optimization using evolutionary algorithms / Kalyanmoy Deb
Tipo de material:
TextoSeries Detalles de publicación: West Sussex, United Kingdom : John Wiley [and] Sons, c2001Edición: 1a edDescripción: xix, 515 p. : il. ; 25 cmISBN: - 9780470743614
- QA 402 .5 D2861
| Tipo de ítem | Biblioteca actual | Biblioteca de origen | Colección | Signatura topográfica | Copia número | Estado | Notas | Fecha de vencimiento | Código de barras | Reserva de ítems | |
|---|---|---|---|---|---|---|---|---|---|---|---|
Libros para consulta en sala
|
Biblioteca Antonio Enriquez Savignac | Biblioteca Antonio Enriquez Savignac | COLECCIÓN RESERVA | QA 402 .5 D2861 (Navegar estantería(Abre debajo)) | 1 | Tránsito | Ing. Telematica | 021914 |
Navegando Biblioteca Antonio Enriquez Savignac estanterías, Colección: COLECCIÓN RESERVA Cerrar el navegador de estanterías (Oculta el navegador de estanterías)
| No hay imagen de cubierta disponible | ||||||||
| QA402 O6718 Señales y sistemas / | QA402 S6518 Señales y Sistemas: Continuos y Discretos / | QA 402 .5 A72 2009 Algoritmos evolutivos : un enfoque práctico / | QA 402 .5 D2861 Multi-objective optimization using evolutionary algorithms / | QA 402 .5 P21 1998 Combinatorial optimization : algorithms and complexity / | QA 402 .5 S99 2006 Discrete optimization algorithms : with Pascal programs / | QA 402 .6 V44 The vehicle routing problem : latest advances and new challenges / |
Incluye referencias bibliográficas: p. [489]-508 e índice
Prologue - Multi-Objective Optimization - Classical Methods - Evolutionary Algorithms - Non-Elitist Multi-Objective Evolutionary Algorithms - Elitist Multi-Objective Evolutionary Algorithms - Constrained Multi-Objective Evolutionary Algorithms - Salient Issues of Multi-Objective Evolutionary Algorithms - Application of Multi-Objective Evolutionary Algorithms
"Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run. · Comprehensive coverage of this growing area of research · Carefully introduces each algorithm with examples and in-depth discussion · Includes many applications to real-world problems, including engineering design and scheduling · Includes discussion of advanced topics and future research · Can be used as a course text or for self-study · Accessible to those with limited knowledge of classical multi-objective optimization and evolutionary algorithms The integrated presentation of theory, algorithms and examples will benefit those working and researching in the areas of optimization, optimal design and evolutionary computing. This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study."--Biblioteca del Congreso (Estados Unidos)
Fondos de la Universidad Compra 100324 1080.00
