The concept of parameter-space size adjustment is proposed in order to enable successful application of genetic algorithms to continuous optimization problems. Performance of genetic algorithms with six different combinations of selection and reproduction mechanisms, with and without parameter-space size adjustment, were severely tested on eleven multiminima test functions. An algorithm with the best performance was employed for the determination of the model parameters of the optical constants of Pt, Ni and Cr.link_to_subscribed_fulltex
In this paper a new genetic algorithm called the Breeder Genetic Algorithm (BGA) is introduced. The ...
The behavior of the two-point crossover operator, on candidate solutions to an optimization problem ...
[[abstract]]According to the results of previous research, the genetic algorithm (GA) is a good tech...
The concept of parameter-space size adjustment is pn,posed in order to enable successful application...
In this paper we propose parameter space size adjustment in genetic algorithms. The performance of t...
The elite genetic algorithm with adaptive mutations is proposed as a tool for solving continuous opt...
The elite genetic algorithm with adaptive mutations is applied to two different continuous optimizat...
This paper is concerned with the problem of adapting the optimization algorithms to the dimension of...
Abstract. This paper is concerned with the problem of adapting the optimization algorithms to the di...
Use of non-deterministic algorithms for solving multi-variable optimization problems is widely used ...
This paper describes a two-space genetic algorithm that finds solutions to minimax optimization prob...
ABSTRACT By the advances in the Evolution Algorithms (EAs) and the intelligent optimization methods...
A genetic algorithm approach suitable for solving multi-objective optimization problems is described...
This paper describes a new approach for parameter optimization that uses a novel representation for...
<p>Each line represents a different set of parameters. The optimization algorithm has successfully c...
In this paper a new genetic algorithm called the Breeder Genetic Algorithm (BGA) is introduced. The ...
The behavior of the two-point crossover operator, on candidate solutions to an optimization problem ...
[[abstract]]According to the results of previous research, the genetic algorithm (GA) is a good tech...
The concept of parameter-space size adjustment is pn,posed in order to enable successful application...
In this paper we propose parameter space size adjustment in genetic algorithms. The performance of t...
The elite genetic algorithm with adaptive mutations is proposed as a tool for solving continuous opt...
The elite genetic algorithm with adaptive mutations is applied to two different continuous optimizat...
This paper is concerned with the problem of adapting the optimization algorithms to the dimension of...
Abstract. This paper is concerned with the problem of adapting the optimization algorithms to the di...
Use of non-deterministic algorithms for solving multi-variable optimization problems is widely used ...
This paper describes a two-space genetic algorithm that finds solutions to minimax optimization prob...
ABSTRACT By the advances in the Evolution Algorithms (EAs) and the intelligent optimization methods...
A genetic algorithm approach suitable for solving multi-objective optimization problems is described...
This paper describes a new approach for parameter optimization that uses a novel representation for...
<p>Each line represents a different set of parameters. The optimization algorithm has successfully c...
In this paper a new genetic algorithm called the Breeder Genetic Algorithm (BGA) is introduced. The ...
The behavior of the two-point crossover operator, on candidate solutions to an optimization problem ...
[[abstract]]According to the results of previous research, the genetic algorithm (GA) is a good tech...