Search results for "evolutionary"

showing 10 items of 4392 documents

Implementing some Evolutionary Computing Methods for Determining the Optimal Parameters in the Turning Process

2015

In this paper, we comparatively present two heuristics search methods – Simulated Annealing and Weighted Sum Genetic Algorithm, in order to find optimal cutting parameters in turning operation. We consider five different constraints aiming to achieve minimum total cost of machining. We developed a customizable software application in Microsoft Visual Studio with C# source code, flexible and extensible that implements the optimization methods. The experiments are based on real data gathered from S.C. “Compa” S.A Sibiu, a company that manufactures automotive components and targets improving of product quality and reducing cost and production time. The obtained results show that, although the …

Mathematical optimizationEngineeringSource codebusiness.industrymedia_common.quotation_subjectGeneral MedicineMachine learningcomputer.software_genreAdaptive simulated annealingEvolutionary computationMicrosoft Visual StudioSoftwareSimulated annealingGenetic algorithmArtificial intelligenceHeuristicsbusinesscomputermedia_commonApplied Mechanics and Materials
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A NEW REPRESENTATION OF ENERGY STORAGE SYSTEMS OPERATION USING FOURIER THEORY IN OPTIMAL SMART GRIDS MANAGEMENT

2012

This paper investigates the possibility to use a new modeling of Energy Storage Systems based on zero integral functions. Such functions represent the course of the energy level stored in batteries during the solution of optimal management problems in smart-grids. Storage devices, such as all the other components that are required to meet an integral capacity constraint along the dispatch time, must show the same State of Charge at the start and at the end of the timeframe considered for operation. In this paper, a set of sinusoidal functions have been used for the synthesis of the charge and discharge course of energy Storage Systems. Such representation allows to eliminate the difficult c…

Mathematical optimizationEngineeringbusiness.industryEnergy storageEvolutionary computationConstraint (information theory)integral constraints optimal management distributed energy resources multi-objective evolutionary optimization smart grids.Settore ING-IND/33 - Sistemi Elettrici Per L'Energiasymbols.namesakeSmart gridState of chargeFourier analysissymbolsbusinessRepresentation (mathematics)Energy (signal processing)
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Voltage Regulation and Power Losses Minimization in Automated Distribution Networks by an Evolutionary Multiobjective Approach

2004

In this paper, the problem of voltage regulation and power losses minimization for automated distribution systems is dealt with. The classical formulation of the problem of optimal control of shunt capacitor banks and Under Load Tap Changers located at HV/MV substations has been coupled with the optimal control of tie-switches and capacitor banks on the feeders of a large radially operated meshed distribution system with the aim of attaining minimum power losses and the flattening of the voltage profile. The considered formulation requires the optimization of two different objectives; therefore the use of adequate multiobjective heuristic optimization methods is needed. The heuristic strate…

Mathematical optimizationEngineeringbusiness.industryFuzzy setEnergy Engineering and Power TechnologyOptimal controlEvolutionary computationFlatteninglaw.inventionSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaCapacitorOptimal control optimization methods power distribution voltage control.Control theorylawMinificationVoltage regulationElectrical and Electronic EngineeringbusinessVoltage
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A new formulation of the optimal compensation and reconfiguration problem including minimum load nodes unavailability for automated distribution netw…

2004

This paper deals with a new formulation of the optimal operation of electrical distribution networks problem in regular working state. In the new deregulated energy market providing reliable and economical service to customers is a primary task. The multiobjective formulation of the reconfiguration and compensation problem used in this paper considers as a primary object also the minimisation of the load nodes unavailability (UA) expressed in probabilistic terms. Therefore, the objectives to be attained through the optimisation strategy are: minimal power losses operation, minimum UA of the load nodes, load balancing among the HV/MV transformers, and voltage profile regularisation. The appl…

Mathematical optimizationEngineeringfeeder reconfigurationbusiness.industryElectric power distributionApplied MathematicsProbabilistic logicEvolutionary algorithmControl reconfigurationComputer Science Applicationslaw.inventionDistributed power generationSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaCapacitorComputational Theory and MathematicslawElectronic engineeringEnergy marketElectrical and Electronic EngineeringUnavailabilityTransformerbusinessRemote control
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AMaLGaM IDEAs in noiseless black-box optimization benchmarking

2009

This paper describes the application of a Gaussian Estimation-of-Distribution (EDA) for real-valued optimization to the noiseless part of a benchmark introduced in 2009 called BBOB (Black-Box Optimization Benchmarking). Specifically, the EDA considered here is the recently introduced parameter-free version of the Adapted Maximum-Likelihood Gaussian Model Iterated Density-Estimation Evolutionary Algorithm (AMaLGaM-IDEA). Also the version with incremental model building (iAMaLGaM-IDEA) is considered.

Mathematical optimizationGaussianComputer Science::Neural and Evolutionary ComputationMathematicsofComputing_NUMERICALANALYSISEvolutionary algorithmBenchmarkingEvolutionary computationsymbols.namesakeIterated functionBlack boxBenchmark (computing)symbolsIncremental build modelMathematicsProceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
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2021

One of the problems that hinder emergency in developing countries is the problem of monitoring a number of activities on inter-urban roadway networks. In the literature, the use of control points is proposed in the context of these countries in order to ensure efficient monitoring, by ensuring a good coverage while minimizing the installation costs as well as the number of accidents across these road networks. In this work, we propose an optimal deployment of these control points from several optimization methods based on some evolutionary multi-objective algorithms: the non-dominated sorting genetic algorithm-II (NSGA-II); the multi-objective particle swarm optimization (MOPSO); the streng…

Mathematical optimizationGeneral Computer ScienceComputer scienceSortingEvolutionary algorithmPareto principleParticle swarm optimizationComputingMilieux_LEGALASPECTSOFCOMPUTINGContext (language use)Multi-objective optimizationSoftware deployment11. SustainabilityElectrical and Electronic EngineeringIntelligent transportation systemInternational Journal of Electrical and Computer Engineering (IJECE)
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A hybrid metaheuristic for the cyclic antibandwidth problem

2013

We propose a hybrid artificial bee colony algorithm for the cyclic antibandwidth problem.We present a computational comparison of different parameter settings.We derive a fine-tuning hybrid artificial bee colony algorithm.The proposal is very competitive with the state-of-the-art algorithm for the cyclic antibandwidth problem. In this paper, we propose a hybrid metaheuristic algorithm to solve the cyclic antibandwidth problem. This hard optimization problem consists of embedding an n-vertex graph into the cycle Cn, such that the minimum distance (measured in the cycle) of adjacent vertices is maximized. It constitutes a natural extension of the well-known antibandwidth problem, and can be v…

Mathematical optimizationInformation Systems and ManagementOptimization problemComputer sciencebusiness.industryComputer Science::Neural and Evolutionary ComputationForagingInitializationDuality (optimization)Swarm intelligenceTabu searchGraphManagement Information SystemsArtificial bee colony algorithmArtificial IntelligenceGraph (abstract data type)Local search (optimization)businessMetaheuristicSoftwareKnowledge-Based Systems
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Path relinking and GRG for artificial neural networks

2006

Artificial neural networks (ANN) have been widely used for both classification and prediction. This paper is focused on the prediction problem in which an unknown function is approximated. ANNs can be viewed as models of real systems, built by tuning parameters known as weights. In training the net, the problem is to find the weights that optimize its performance (i.e., to minimize the error over the training set). Although the most popular method for training these networks is back propagation, other optimization methods such as tabu search or scatter search have been successfully applied to solve this problem. In this paper we propose a path relinking implementation to solve the neural ne…

Mathematical optimizationInformation Systems and ManagementTraining setGeneral Computer ScienceArtificial neural networkComputer sciencebusiness.industryManagement Science and Operations ResearchSolverIndustrial and Manufacturing EngineeringBackpropagationEvolutionary computationTabu searchNonlinear programmingSearch algorithmModeling and SimulationArtificial intelligencebusinessMetaheuristicEuropean Journal of Operational Research
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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…

Mathematical optimizationIntegral constraintMulti-objective evolutionary algorithmbusiness.industryComputer scienceFourier analysiEconomic dispatchSmart gridsMulti-objective optimizationEnergy storageElectrical energy storage systemSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaSettore ING-IND/31 - ElettrotecnicaSmart gridDistributed generationComponent (UML)Optimal dispatch of resourcebusinessRepresentation (mathematics)SoftwareEnergy (signal processing)Applied Soft Computing
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Improving Computing Systems Automatic Multiobjective Optimization Through Meta-Optimization

2016

This paper presents the extension of framework for automatic design space exploration (FADSE) tool using a meta-optimization approach, which is used to improve the performance of design space exploration algorithms, by driving two different multiobjective meta-heuristics concurrently. More precisely, we selected two genetic multiobjective algorithms: 1) non-dominated sorting genetic algorithm-II and 2) strength Pareto evolutionary algorithm 2, that work together in order to improve both the solutions’ quality and the convergence speed. With the proposed improvements, we ran FADSE in order to optimize the hardware parameters’ values of the grid ALU processor (GAP) micro-architecture from a b…

Mathematical optimizationMeta-optimizationComputer scienceCycles per instructionDesign space explorationPareto principleSortingEvolutionary algorithm02 engineering and technologyComputer Graphics and Computer-Aided DesignMulti-objective optimization020202 computer hardware & architecture0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingAlgorithm designElectrical and Electronic EngineeringSoftwareIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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