Search results for " Evolutionary algorithm"
showing 8 items of 8 documents
GenClust: A genetic algorithm for clustering gene expression data
2005
Abstract Background Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designed and validated for the task. Despite the widespread use of artificial intelligence techniques in bioinformatics and, more generally, data analysis, there are very few clustering algorithms based on the genetic paradigm, yet that paradigm has great potential in finding good heuristic solutions to a difficult optimization problem such as clustering. Results GenClust is a new genetic algorithm for clustering gene expression data. It has two key features: (a) a novel coding of the search space that is simple, …
A genetic integrated fuzzy classifier
2005
This paper introduces a new classifier, that is based on fuzzy-integration schemes controlled by a genetic optimisation procedure. Two different types of integration are proposed here, and are validated by experiments on real data sets of biological cells. The performance of our classifier is tested against a feed-forward neural network and a Support Vector Machine. Results show the good performance and robustness of the integrated classifier strategies.
Modelling energy storage systems using Fourier analysis: An application for smart grids optimal management
2014
In this paper, a new and efficient model for variables representation, named F-coding, in optimal power dispatch problems for smart electrical distribution grids is proposed. In particular, an application devoted to optimal energy dispatch of Distributed Energy Resources including ideal storage devices is here considered. Electrical energy storage systems, such as any other component that must meet an integral capacity constraint in optimal dispatch problems, have to show the same energy level at the beginning and at the end of the considered timeframe for operation. The use of zero-integral functions, such as sinusoidal functions, for the synthesis of the charge and discharge course of bat…
A Generalized Framework for Optimal Sizing of Distributed Energy Resources in Micro-Grids Using an Indicator-Based Swarm Approach
2014
In this paper, a generalized double-shell framework for the optimal design of systems managed optimally according to different criteria is developed. Optimal design is traditionally carried out by means of minimum capital and management cost formulations and does not typically consider optimized operation. In this paper, the optimized multiobjective management is explicitly considered into the design formulation. The quality of each design solution is indeed defined by the evaluation of operational costs and capital costs. Besides, the assessment of the operational costs term is deduced by means of the solution of a multiobjective optimization problem. Each design solution is evaluated usin…
A Surrogate-assisted Reference Vector Guided Evolutionary Algorithm for Computationally Expensive Many-objective Optimization
2018
We propose a surrogate-assisted reference vector guided evolutionary algorithm for computationally expensive optimization problems with more than three objectives. The proposed algorithm is based on a recently developed evolutionary algorithm for many-objective optimization that relies on a set of adaptive reference vectors for selection. The proposed surrogateassisted evolutionary algorithm uses Kriging to approximate each objective function to reduce the computational cost. In managing the Kriging models, the algorithm focuses on the balance of diversity and convergence by making use of the uncertainty information in the approximated objective values given by the Kriging models, the distr…
A Memetic Island Model for Discrete Tomography Reconstruction
2011
Soft computing is a term indicating a coalition of methodologies, and its basic dogma is that, in general, better results can be obtained through the use of constituent methodologies in combination, rather than in a stand alone mode. Evolutionary computing belongs to this coalition, and thus memetic algorithms. Here, we present a combination of several instances of a recently proposed memetic algorithm for discrete tomography reconstruction, based on the island model parallel implementation. The combination is motivated by the fact that, even though the results of the recently proposed approach are finally better and more robust compared to other approaches, we advised that its major drawba…
Spectral phase reconstruction of femtosecond laser pulse from interferometric autocorrelation and evolutionary algorithm
2021
International audience; We report on the complete temporal characterization of femtosecond laser pulses from second-order interferometric autocorrelation and laser spectrum measurements. The method exploits a newly developed autocorrelator based on a two photon-absorption signal produced directly within a camera sensor so as to provide a single-shot interferometric autocorrelation of great reliability and robustness. Interferometric autocorrelation trace and laser spectrum are exploited for a spectral phase retrieval via an evolutionary algorithm. The quality of the reconstruction for highly modulated spectral phases imprinted by a pulse shaper confirms the reliability of the method. The au…
Synchronous R-NSGA-II: An Extended Preference-Based Evolutionary Algorithm for Multi-Objective Optimization
2015
Classical evolutionary multi-objective optimization algorithms aim at finding an approx- imation of the entire set of Pareto optimal solutions. By considering the preferences of a decision maker within evolutionary multi-objective optimization algorithms, it is possible to focus the search only on those parts of the Pareto front that satisfy his/her preferences. In this paper, an extended preference-based evolutionary algorithm has been proposed for solving multi-objective optimiza- tion problems. Here, concepts from an interactive synchronous NIMBUS method are borrowed and combined with the R-NSGA-II algorithm. The proposed synchronous R-NSGA-II algorithm uses preference information provid…