Genetic Algorithm Epub

Network Models and Optimization: Multiobjective Genetic Algorithm Approach (repost)

Mitsuo Gen, Runwei Cheng, Lin Lin, "Network Models and Optimization: Multiobjective Genetic Algorithm Approach"
English | 2008 | ISBN: 1848001800 | 692 pages | PDF | 26,2 MB

Network models are critical tools in business, management, science and industry. Network Models and Optimization: Multiobjective Genetic Algorithm Approach presents an insightful, comprehensive, and up-to-date treatment of multiple objective genetic algorithms to network optimization problems in many disciplines, such as engineering, computer science, operations research, transportation, telecommunication, and manufacturing.
Network Models and Optimization: Multiobjective Genetic Algorithm Approach (Repost)

Network Models and Optimization: Multiobjective Genetic Algorithm Approach
Publisher: Springer | ISBN: 1848001800 | edition 2008 | PDF | 692 pages | 16,5 mb

Network models are critical tools in business, management, science and industry. Network Models and Optimization: Multiobjective Genetic Algorithm Approach presents an insightful, comprehensive, and up-to-date treatment of multiple objective genetic algorithms to network optimization problems in many disciplines, such as engineering, computer science, operations research, transportation, telecommunication, and manufacturing.
Network Models and Optimization: Multiobjective Genetic Algorithm Approach (Repost)

Mitsuo Gen, Runwei Cheng, Lin Lin, "Network Models and Optimization: Multiobjective Genetic Algorithm Approach"
2008 | pages: 701 | ISBN: 1848001800 | PDF | 26,2 mb
Network Models and Optimization: Multiobjective Genetic Algorithm Approach (repost)

Network Models and Optimization: Multiobjective Genetic Algorithm Approach
Sp ger | 2008 | ISBN: 1848001800 | 692 pages | PDF | 26,2 MB
Network Models and Optimization: Multiobjective Genetic Algorithm Approach (repost)

Mitsuo Gen, Runwei Cheng, Lin Lin, "Network Models and Optimization: Multiobjective Genetic Algorithm Approach"
Sp ger | 2008 | ISBN: 1848001800 | 692 pages | PDF | 26,2 MB
"Optimizing Hydrocarbon Field Development Using a Genetic Algorithm Based Approach" by Antonio Carlos Bittencourt

"Optimizing Hydrocarbon Field Development Using a Genetic Algorithm Based Approach" by Antonio Carlos Bittencourt
Stanford University | 1997 | ISBN: n/a | 167 pages | PDF | 5 Mb

This work concerns the optimization of characteristic petroleum problems considering economic factors. A hybrid algorithm based on direct methods such as Genetic Algorithm, polytope search method, Tabu Search and memory strategy is presented. Hybrid techniques were found to improve the overall method.
Network Models and Optimization: Multiobjective Genetic Algorithm Approach

Mitsuo Gen, Runwei Cheng, Lin Lin " Network Models and Optimization: Multiobjective Genetic Algorithm Approach"
Springer | 2008-07-29 | ISBN: 1848001800 | 692 pages | PDF | 16,4 MB

Genetic Algorithms with Python  eBooks & eLearning

Posted by AlenMiler at Nov. 20, 2016
Genetic Algorithms with Python

Genetic Algorithms with Python by Clinton Sheppard
English | 29 Apr. 2016 | ISBN: 1540324001 | 282 Pages | MOBI/EPUB/PDF | 4.49 MB

Get a hands-on introduction to machine learning with genetic algorithms using Python. Step-by-step tutorials build your skills from Hello World! to optimizing one genetic algorithm with another, and finally genetic programming; thus preparing you to apply genetic algorithms to problems in your own field of expertise.

Introduction to Genetic Algorithms by S. N. Deepa [Repost]  

Posted by tanas.olesya at Dec. 6, 2014
Introduction to Genetic Algorithms by S. N. Deepa [Repost]

Introduction to Genetic Algorithms by S. N. Deepa
English | December 12, 2007 | ISBN: 354073189X | 453 pages | PDF | 9 MB

This book offers a basic introduction to genetic algorithms. It provides a detailed explanation of genetic algorithm concepts and examines numerous genetic algorithm optimization problems. In addition, the book presents implementation of optimization problems using C and C++ as well as simulated solutions for genetic algorithm problems using MATLAB 7.0. It also includes application case studies on genetic algorithms in emerging fields.

Classification and Learning Using Genetic Algorithms  

Posted by tanas.olesya at Feb. 11, 2016
Classification and Learning Using Genetic Algorithms

Classification and Learning Using Genetic Algorithms: Applications in Bioinformatics and Web Intelligence by Sanghamitra Bandyopadhyay
English | 23 Apr. 2007 | ISBN: 3540496068 | 320 Pages | PDF | 6 MB

This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. It examines how a search technique, the genetic algorithm, can be used for pattern classification mainly through approximating decision boundaries.