Intelligent Optimisation Techniques

Author: D.T. Pham
Edition: 1
Binding: Hardcover
ISBN: 1852330287

Intelligent Optimisation Techniques

This book covers four optimisation techniques loosely classified as intelligent: genetic algorithms, tabu search, simulated annealing and neural networks. Get Intelligent Optimisation Techniques computer books for free.
Genetic algorithms locate optima using processes similar to those in natural selection and genetics. Tabu search is a heuristic procedure that employs dynamically generated constraints or tabus to guide the search for optimum solutions. Simulated annealing find optima in a way analogous to the reaching of minimum energy configurations in metal annealing. Neural networks are computational models of the brain. Certain types of neural networks can be used for optimisation by exploiting their inherent ability to evolve in the direction of the negative gradient of an energy function and to reach Check Intelligent Optimisation Techniques our best computer books for 2013. All books are available in pdf format and downloadable from rapidshare, 4shared, and mediafire.

Intelligent Optimisation Techniques Free

Genetic algorithms locate optima using processes similar to those in natural selection and genetics. Tabu search is a heuristic procedure that employs dynamically generated constraints or tabus to guide the search for optimum solutions. Simulated annealing find optima in a way analogous to the reaching of minimum energy configurations in metal annealing. Neural networks are computational models of the brain enetic algorithms locate optima using processes similar to those in natural selection and genetics. Tabu search is a heuristic procedure that employs dynamically generated constraints or tabus to guide the search for optimum solutions. Simulated annealing find optima in a way analogous to the reaching of minimum energy configurations in metal annealing. Neural networks are computational models of the brain. Certain types of neural networks can be used for optimisation by exploiting their inherent ability to evolve in the direction of the negative gradient of an energy function and to reach

Related Computer Books