Search results for "Programming"

showing 10 items of 3090 documents

A general framework for a class of non-linear approximations with applications to image restoration

2018

Este artículo se encuentra disponible en la página web de la revista en la siguiente URL: https://www.sciencedirect.com/science/article/abs/pii/S0377042717301188 Este es el pre-print del siguiente artículo: Candela, V., Falcó, A. & Romero, PD. (2018). A general framework for a class of non-linear approximations with applications to image restoration. Journal of Computational and Applied Mathematics, vol. 330 (mar.), pp. 982-994, que se ha publicado de forma definitiva en https://doi.org/10.1016/j.cam.2017.03.008 This is the pre-peer reviewed version of the following article: Candela, V., Falcó, A. & Romero, PD. (2018). A general framework for a class of non-linear approximations with applic…

Mathematical optimization010103 numerical & computational mathematics01 natural sciencesProjection (linear algebra)ConvexityImage (mathematics)symbols.namesakeProgramming (Mathematics) in Works of art.Convergence (routing)Applied mathematics0101 mathematicsProgramación (Matemáticas) - Aplicaciones en Obras de arte.Art - Conservation and restoration.Image restorationMathematicsApplied MathematicsHilbert space.Hilbert spaceAlgoritmos computacionales.Hilbert Espacio de.Linear subspaceComputer algorithms.010101 applied mathematicsComputational MathematicsObras de arte - Restauración.symbolsDeconvolutionObras de arte - Conservación.Journal of Computational and Applied Mathematics
researchProduct

On Constraint Handling in Surrogate-Assisted Evolutionary Many-Objective Optimization

2016

Surrogate-assisted evolutionary multiobjective optimization algorithms are often used to solve computationally expensive problems. But their efficacy on handling constrained optimization problems having more than three objectives has not been widely studied. Particularly the issue of how feasible and infeasible solutions are handled in generating a data set for training a surrogate has not received much attention. In this paper, we use a recently proposed Kriging-assisted evolutionary algorithm for many-objective optimization and investigate the effect of infeasible solutions on the performance of the surrogates. We assume that constraint functions are computationally inexpensive and consid…

Mathematical optimization021103 operations researchComputer scienceFeasible region0211 other engineering and technologiesEvolutionary algorithm02 engineering and technologyConstraint satisfactionMulti-objective optimizationConstraint (information theory)Data set0202 electrical engineering electronic engineering information engineeringBenchmark (computing)020201 artificial intelligence & image processingEvolutionary programming
researchProduct

A branch-and-cut algorithm for the Orienteering Arc Routing Problem

2016

[EN] In arc routing problems, customers are located on arcs, and routes of minimum cost have to be identified. In the Orienteering Arc Routing Problem (OARP),in addition to a set of regular customers that have to be serviced, a set of potential customers is available. From this latter set, customers have to be chosen on the basis of an associated profit. The objective is to find a route servicing the customers which maximize the total profit collected while satisfying a given time limit on the route.In this paper, we describe large families of facet-inducing inequalities for the OARP and present a branch-and-cut algorithm for its solution. The exact algorithm embeds a procedure which builds…

Mathematical optimization021103 operations researchGeneral Computer Science0211 other engineering and technologiesOrienteering02 engineering and technologyManagement Science and Operations ResearchTime limitRouting problems with profitsPolyhedronExact algorithmOrienteering Arc Routing ProblemBranch-and-cutModeling and Simulation0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingDestination-Sequenced Distance Vector routingMATEMATICA APLICADAInteger programmingArc routingAlgorithmBranch and cutMathematicsComputers & Operations Research
researchProduct

A new approach for critical resources allocation

2009

This paper presents a solution based on Artificial Intelligence using Multi-objective Genetic Algorithms to optimize the allocation of teachers and classrooms. The implementation was created in order to optimize the process in both cases, allowing them to compete so as to establish a balance and arrive at a feasible solution quickly and efficiently.

Mathematical optimizationApplication programming interfaceOrder (exchange)Computer scienceProcess (engineering)Resource allocationGenetic operatorFitness score
researchProduct

Portfolios with fuzzy returns: Selection strategies based on semi-infinite programming

2008

AbstractThis paper provides new models for portfolio selection in which the returns on securities are considered fuzzy numbers rather than random variables. The investor's problem is to find the portfolio that minimizes the risk of achieving a return that is not less than the return of a riskless asset. The corresponding optimal portfolio is derived using semi-infinite programming in a soft framework. The return on each asset and their membership functions are described using historical data. The investment risk is approximated by mean intervals which evaluate the downside risk for a given fuzzy portfolio. This approach is illustrated with a numerical example.

Mathematical optimizationApplied MathematicsMathematics::Optimization and ControlEfficient frontierPortfolio selection problemSortino ratioFuzzy mathematical programmingRate of return on a portfolioComputational MathematicsDownside risk functionFuzzy returnsComputer Science::Computational Engineering Finance and ScienceReplicating portfolioCapital asset pricing modelPortfolioPortfolio optimizationSemi-infinite programmingModern portfolio theoryMathematicsJournal of Computational and Applied Mathematics
researchProduct

Complementary Judgment Matrix Method with Imprecise Information for Multicriteria Decision-Making

2018

The complementary judgment matrix (CJM) method is an MCDA (multicriteria decision aiding) method based on pairwise comparisons. As in AHP, the decision-maker (DM) can specify his/her preferences using pairwise comparisons, both between different criteria and between different alternatives with respect to each criterion. The DM specifies his/her preferences by allocating two nonnegative comparison values so that their sum is 1. We measure and pinpoint possible inconsistency by inconsistency errors. We also compare the consistency of CJM and AHP trough simulation. Because preference judgments are always more or less imprecise or uncertain, we introduce a way to represent the uncertainty throu…

Mathematical optimizationArticle SubjectComputer scienceGeneral Mathematicsstokastinen monikriteerinen arvostusanalyysi0211 other engineering and technologiesAnalytic hierarchy processcomparisons02 engineering and technologyMeasure (mathematics)Consistency (database systems)0202 electrical engineering electronic engineering information engineeringuncertainty levelsPreference (economics)ta512päätösteoriaStochastic multicriteria acceptability analysis021103 operations researchta214complementary judgment matrix (CJM) methodlcsh:MathematicsRank (computer programming)ta111General EngineeringMultiple-criteria decision analysislcsh:QA1-939epävarmuuslcsh:TA1-2040stochastic multicriteria acceptability analysis (SMAA)020201 artificial intelligence & image processingPairwise comparisonlcsh:Engineering (General). Civil engineering (General)multicriteria decision-makingmatriisit
researchProduct

State-Feedback Stabilization for a Class of Stochastic Feedforward Nonlinear Time-Delay Systems

2013

We investigate the state-feedback stabilization problem for a class of stochastic feedforward nonlinear time-delay systems. By using the homogeneous domination approach and choosing an appropriate Lyapunov-Krasovskii functional, the delay-independent state-feedback controller is explicitly constructed such that the closed-loop system is globally asymptotically stable in probability. A simulation example is provided to demonstrate the effectiveness of the proposed design method.

Mathematical optimizationClass (computer programming)Article SubjectApplied Mathematicslcsh:MathematicsFeed forwardState (functional analysis)lcsh:QA1-939Nonlinear systemControl theoryHomogeneousStability theoryAnalysisMathematicsAbstract and Applied Analysis
researchProduct

The Multiple Multidimensional Knapsack with Family-Split Penalties

2021

Abstract The Multiple Multidimensional Knapsack Problem with Family-Split Penalties (MMdKFSP) is introduced as a new variant of both the more classical Multi-Knapsack and Multidimensional Knapsack Problems. It reckons with items categorized into families and where if an individual item is selected to maximize the profit, all the items of the same family must be selected as well. Items belonging to the same family can be assigned to different knapsacks; however, in this case, split penalties are incurred. This problem arises in resource management of distributed computing contexts and Service Oriented Architecture environments. An exact algorithm based on the exploitation of a specific combi…

Mathematical optimizationCombinatorial optimizationInformation Systems and ManagementGeneral Computer ScienceComputer scienceKnapsack Problem0211 other engineering and technologiesBenders’ cuts; Combinatorial optimization; Integer programming; Knapsack Problems; Resource assignmentResource assignment02 engineering and technologyManagement Science and Operations ResearchIndustrial and Manufacturing Engineering0502 economics and businessInteger programming050210 logistics & transportation021103 operations research05 social sciencesBenders’ cutInteger programmingSolverKnapsack ProblemsBenders’ cutsExact algorithmKnapsack problemModeling and SimulationCombinatorial optimizationEuropean Journal of Operational Research
researchProduct

GRASP with path relinking heuristics for the antibandwidth problem

2010

This article proposes a linear integer programming formulation and several heuristics based on GRASP and path relinking for the antibandwidth problem. In the antibandwidth problem, one is given an undirected graph with n nodes and must label the nodes in a way that each node receives a unique label from the set {1, 2,…,n}, such that, among all adjacent node pairs, the minimum difference between the node labels is maximized. Computational results show that only small instances of this problem can be solved exactly (to optimality) with a commercial integer programming solver and that the heuristics find high-quality solutions in much less time than the commercial solver. © 2010 Wiley Periodic…

Mathematical optimizationComputer Networks and CommunicationsGRASPSolverSet (abstract data type)Hardware and ArchitecturePath (graph theory)Node (circuits)HeuristicsInteger programmingMetaheuristicSoftwareInformation SystemsMathematicsNetworks
researchProduct

A Simplified Analytical Approach for Optimal Planning of Distributed Generation in Electrical Distribution Networks

2019

DG-integrated distribution system planning is an imperative issue since the installing of distributed generations (DGs) has many effects on the network operation characteristics, which might cause significant impacts on the system performance. One of the most important characteristics that mostly varies because of the installation of DG units is the power losses. The parameters affecting the value of the power losses are number, location, capacity, and power factor of the DG units. In this paper, a new analytical approach is proposed for optimally installing DGs to minimize power loss in distribution networks. Different parameters of DG are considered and evaluated in order to achieve a hig…

Mathematical optimizationComputer science020209 energydistribution systems02 engineering and technologyPower factorReduction (complexity)Softwareoptimum DG capacity0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceMATLABInstrumentationSIMPLE algorithmcomputer.programming_languageFluid Flow and Transfer Processesdistributed generationbusiness.industryProcess Chemistry and Technology020208 electrical & electronic engineeringGeneral EngineeringProcess (computing)Computer Science ApplicationsPower (physics)Settore ING-IND/33 - Sistemi Elettrici Per L'EnergiaDistribution systemDistributed generationoptimum DG locationbusinesscomputerApplied Sciences
researchProduct