General Architecture for Hardware Implementation of Genetic Algorithm

2006 ◽  
Author(s):  
Tatsuhiro Tachibana ◽  
Yoshihiro Murata ◽  
Naoki Shibata ◽  
Keiichi Yasumoto ◽  
Minoru Ito
Keyword(s):  
Genetic Algorithm ◽  
Hardware Implementation ◽  
General Architecture

Hardware implementation of the elitist compact Genetic Algorithm using Cellular Automata pseudo-random number generator

2013 ◽  
Vol 39 (4) ◽  
pp. 1367-1379 ◽  
Author(s):  
Marco A. Moreno-Armendáriz ◽  
Nareli Cruz-Cortés ◽  
Carlos A. Duchanoy ◽  
Alejandro León-Javier ◽  
Rolando Quintero
Keyword(s):  
Genetic Algorithm ◽  
Cellular Automata ◽  
Hardware Implementation ◽  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Compact Genetic Algorithm ◽  
Pseudo Random Number Generator

Hardware Implementation of AES Based on Genetic Algorithm

2006 ◽  
pp. 904-907
Author(s):  
Li Wang ◽  
Youren Wang ◽  
Rui Yao ◽  
Zhai Zhang
Keyword(s):  
Genetic Algorithm ◽  
Hardware Implementation

A Novel Hardware Implementation of the Compact Genetic Algorithm

2010 ◽  
Author(s):  
Marco A. Moreno-Armendariz ◽  
Nareli Cruz-Cortes ◽  
Alejandro Leon-Javier
Keyword(s):  
Genetic Algorithm ◽  
Hardware Implementation ◽  
Compact Genetic Algorithm

scholarly journals New Hardware Engine for New Operating Systems

2013 ◽  
Vol 5 ◽  
pp. 16-26
Author(s):  
Nazjla Ahmadi ◽  
Mehrad Kaveh
Keyword(s):  
Genetic Algorithm ◽  
Genetic Diversity ◽  
Operating Systems ◽  
Hardware Implementation ◽  
Global Optimum ◽  
Local Optimum ◽  
Genetic Operators ◽  
Soft Computing Method ◽  
Software Implementations ◽  
Computing Method

Genetic algorithm is a soft computing method that works on set of solutions. These solutions are called chromosome and the best one is the absolute solution of the problem. The main problem of this algorithm is that after passing through some generations, it may be produced some chromosomes that had been produced in some generations ago that causes reducing the convergence speed. From another respective, most of the genetic algorithms are implemented in software and less works have been done on hardware implementation. Our work implements genetic algorithm in hardware that doesn’t produce chromosome that have been produced in previous generations. In this work, most of genetic operators are implemented without producing iterative chromosomes and genetic diversity is preserved. Genetic diversity causes that not only don’t this algorithm converge to local optimum but also reaching to global optimum. Without any doubts, proposed approach is so faster than software implementations. Evaluation results also show the proposed approach is faster than hardware ones.

scholarly journals Hardware implementation of a novel genetic algorithm

2007 ◽  
Vol 71 (1-3) ◽  
pp. 95-106 ◽  
Author(s):  
Z. Zhu ◽  
D.J. Mulvaney ◽  
V.A. Chouliaras
Keyword(s):  
Genetic Algorithm ◽  
Hardware Implementation
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