Name: Ant Colony Optimization: Methods and Applications (en Inglés)
Price: 3391.87 MXN
Availability: InStock
Author: Ostfeld, AVI
ISBN: 9789533071572

Envío gratis

portada Ant Colony Optimization: Methods and Applications (en Inglés)

Formato

Libro Físico

Editorial

Intechopen

Autor

Ostfeld, AVI

Idioma

Inglés

N° páginas

356

Encuadernación

Tapa Dura

Dimensiones

24.4 x 17.0 x 2.1 cm

Peso

0.77 kg.

ISBN13

9789533071572

Categorías

Redes neuronales y sistemas difusos

Ant Colony Optimization: Methods and Applications (en Inglés)

Ostfeld, Avi (Autor) · Intechopen · Tapa Dura

Libro Nuevo

$ 3,391.87

$ 5,653.11

Ahorras: $ 2,261.24

40% descuento

Envío normal

Origen: Estados Unidos (Costos de importación incluídos en el precio)

Se enviará desde nuestra bodega entre el Lunes 12 de Agosto y el Viernes 23 de Agosto.

Lo recibirás en cualquier lugar de México entre 1 y 3 días hábiles luego del envío.

Reseña del libro "Ant Colony Optimization: Methods and Applications (en Inglés)"

Ants communicate information by leaving pheromone tracks. A moving ant leaves, in varying quantities, some pheromone on the ground to mark its way. While an isolated ant moves essentially at random, an ant encountering a previously laid trail is able to detect it and decide with high probability to follow it, thus reinforcing the track with its own pheromone. The collective behavior that emerges is thus a positive feedback: where the more the ants following a track, the more attractive that track becomes for being followed; thus the probability with which an ant chooses a path increases with the number of ants that previously chose the same path. This elementary ant's behavior inspired the development of ant colony optimization by Marco Dorigo in 1992, constructing a meta-heuristic stochastic combinatorial computational methodology belonging to a family of related meta-heuristic methods such as simulated annealing, Tabu search and genetic algorithms. This book covers in twenty chapters state of the art methods and applications of utilizing ant colony optimization algorithms. New methods and theory such as multi colony ant algorithm based upon a new pheromone arithmetic crossover and a repulsive operator, new findings on ant colony convergence, and a diversity of engineering and science applications from transportation, water resources, electrical and computer science disciplines are presented.