Multiobjective Optimization And Genetic Algoritms With Matlab
Download Multiobjective Optimization And Genetic Algoritms With Matlab PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Multiobjective Optimization And Genetic Algoritms With Matlab book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Multiobjective Optimization and Genetic Algoritms with MATLAB
Author: Foster N.
language: en
Publisher: Createspace Independent Publishing Platform
Release Date: 2016-11-12
MATLAB Global Optimization Toolbox provides methods that search for global solutions to problems that contain multiple maxima or minima. It includes global search, multistart, pattern search, genetic algorithm, and simulated annealing solvers. You can use these solvers to solve optimization problems where the objective or constraint function is continuous, discontinuous, stochastic, does not possess derivatives, or includes simulations or black-box functions with undefined values for some parameter settings. Genetic algorithm and pattern search solvers support algorithmic customization. You can create a custom genetic algorithm variant by modifying initial population and fitness scaling options or by defining parent selection, crossover, and mutation functions. You can customize pattern search by defining polling, searching, and other functions. The more important features are de next:* Interactive tools for defining and solving optimization problems and monitoring solution progress* Global search and multistart solvers for finding single or multiple global optima* Genetic algorithm solver that supports linear, nonlinear, and bound constraints* Multiobjective genetic algorithm with Pareto-front identification, including linear and bound constraints* Pattern search solver that supports linear, nonlinear, and bound constraints* Simulated annealing tools that implement a random search method, with options for defining annealing process, temperature schedule, and acceptance criteria* Parallel computing support in multistart, genetic algorithm, and pattern search solver
Multiobjective Evolutionary Algorithms and Applications
Author: Kay Chen Tan
language: en
Publisher: Springer Science & Business Media
Release Date: 2005-05-04
Evolutionary multiobjective optimization is currently gaining a lot of attention, particularly for researchers in the evolutionary computation communities. Covers the authors’ recent research in the area of multiobjective evolutionary algorithms as well as its practical applications.
Neural Networks and Learning Algorithms in MATLAB
Author: Ardashir Mohammadazadeh
language: en
Publisher: Springer Nature
Release Date: 2022-12-10
This book explains the basic concepts, theory and applications of neural networks in a simple unified approach with clear examples and simulations in the MATLAB programming language. The scripts herein are coded for general purposes to be easily extended to a variety of problems in different areas of application. They are vectorized and optimized to run faster and be applicable to high-dimensional engineering problems. This book will serve as a main reference for graduate and undergraduate courses in neural networks and applications. This book will also serve as a main basis for researchers dealing with complex problems that require neural networks for finding good solutions in areas, such as time series prediction, intelligent control and identification. In addition, the problem of designing neural network by using metaheuristics, such as the genetic algorithms and particle swarm optimization, with one objective and with multiple objectives, is presented.