In this paper we study the performance of different evolutionary strategies based on explicit averaging. On a previous study, (Costa et al., 2012) proposed a probabilistic fitness function for an agent model based on neural networks and genetic algorithms employed to investigate the behaviour of rats in an elevated plus-maze (EPM). Differently from other computational models, the virtual rat pr...

In this paper, a new evolutionary scheme to design a TSK fuzzy model from relevant data is proposed. The identification of the antecedent rule parameters is performed via the evolutionary algorithm with the unique fitness function and the various evolutionary operators, while the identification of the consequent parameters is done using the least square method. The occurrence of the multiple ov...

in this paper, multi-objective uniform-diversity genetic algorithm (muga) with a diversity preserving mechanism called the ε-elimination algorithm is used for pareto optimization of 5-degree of freedom vehicle vibration model considering the five conflicting functions simultaneously. the important conflicting objective functions that have been considered in this work are, namely, vertical accel...

1 The LIDIC is supported by the Universidad Nacional de San Luis and the ANPCYT (National Agency to Promote Science and Technology). ABSTRACT Non–stationary, or dynamic, problems change over time. There exist a variety of forms of dynamism. The concept of dynamic environments in the context of this paper means that the fitness landscape changes during the run of an evolutionary algorithm. Genet...

Information Retrieval (IR) System is very complex in nature due to the complex interactions between documents and queries, which means that the matching of document representations and query representations is not straightforward. The Genetic Algorithm (GA) is widely used in IR systems to improve the effectiveness such systems. This study uses the Vector Space Model (VSM) and the Extended Boole...

This article analyses a version of genetic algorithm (GA, Holland 1975) designed for function optimization, which is simple and reliable for most applications. The novelty in current approach is random provision of parameters, created by the GA. Chromosome portions which do not t ranslate into fitness are given function to diversify control parameters for the GA, providing random parameter sett...

A new method based on adaptive GA(genetic algorithm) for optimizing the parameters of CMOS operational amplifier is presented in this paper. The synthesis of the Op-amp (operational amplifier) can be translated into multiple-objective optimization task, in which a large number of specifications have to be taken into account. Such as DC-gain, bandwidth of unity gain, phase-margin, power, noise a...

This paper proposes a novel adaptive sequential niche particle swarm optimization (ASNPSO) algorithm, which uses multiple subswarms to detect optimal solutions sequentially. In this algorithm, the hill valley function is used to determine how to change the fitness of a particle in a sub-swarm run currently. This algorithm has strong and adaptive searching ability. The experimental results show ...

Clustering analysis of the gene expression profiles has been used for identifying the functions of unknown genes. Fuzzy clustering method, which is one category of clustering, assigns one sample to multiple clusters as their degrees of membership. It is more appropriate for analyzing gene expression profiles because genes usually belong to multiple functional families. However, general clusteri...

in this paper proposes a fuzzy multi-objective hybrid genetic and bee colony optimization algorithm(ga-bco) to find the optimal restoration of loads of power distribution network under fault.restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. to improve the efficiency of restoration and facilitate theactivity...