In this work we present an application of the Confidence Interval Based Crossover using L2 Norm (CIXL2) and BLX-α crossovers to the evolution of neural networks. CIXL2 is a new crossover operator, based on obtaining the statistical features of the best individuals of the population. These features are used as virtual parents for the crossover operator. Due to the permutation problem of neural n...

Different kinds of genetic algorithms have been investigated for a parameter identification of a fermentation process. Altogether eight realizations of genetic algorithms have been presented four of simple genetic algorithms and four of multi-population ones. Each of them is characterized with a different sequence of implementation of main genetic operators, namely selection, crossover and muta...

The selection operator in the standard genetic algorithm (GA) determines which individuals are chosen from a relatively homologous population for mating and crossover. This operator is crucial for the performance of the GA, since it may lead the algorithm to premature convergence and limited search scope (or genetic diversity) by repeatedly choosing very strong individuals with similar genetic ...

Genetic algorithms are biological inspired search procedures that have been used to solve different hard problems. They are based on the neo-Darwinian ideas of natural selection and reproduction. Since Holland proposals back in 1975, two main genetic operators, crossover and mutation, have been explored with success. Nevertheless, in nature there exist much more mechanisms for genetic recombina...

Genetic algorithms are adaptive systems biologically motivated which have been used to solve different problems. Since Holland's proposals back in 1975, two main genetic operators, crossover and mutation, have been explored with success. Nonetheless, nature presents many other mechanisms of genetic recombination, based on phenomena like gene insertion, duplication or movement. The aim of this p...

The microarray data classification problem is a recent complex pattern recognition problem. The most important goal in supervised classification of microarray data, is to select a small number of relevant genes from the initial data in order to obtain high predictive classification accuracy. With the framework of a hybrid filter-wrapper, we study in this paper the role of the multi-parent recom...

In recent years, the genetic programming crossover operator has been criticized on both theoretical and empirical grounds. This paper introduces a new crossover operator for linear genomes that encourages the emergence of positional homology in the population. Preliminary experimental results suggest that this approach is a promising direction for redesign of the mechanism of crossover.

Open vehicle routing problem with single and mixed fleet strategy is logistics optimization indispensable part. Hybrid genetic algorithm is used to optimize the solution. Firstly, use sequence of real numbers coding so as to simplify the problem; construct the targeted initial solution to improve the feasibility; adopt some arithmetic crossover operator to enhance whole search ability of the ch...

Turning to Renewable Energy Sources (RES) is the most logical politics in securing the modern society from critical changes in earth increasing temperature. However, Distributed Generation (DG) sources could lead to new challenges in electricity network, mainly allocation of DG sources in distribution level of power system will set the existing network under stress of power flow parameters. The...

This paper presents a new genetic operator called adaptive operator to improve local portions of chromosomes. This new operator is implemented into PseudoBacterial Genetic Algorithm (PBGA). The PBGA was proposed by the authors as a new approach combining a genetic algorithm (GA) with a local improvement mechanism inspired by a process in bacterial genetics. The PBGA was applied for the acquisit...