Search results for "resolution"

showing 10 items of 1928 documents

Heuristics for the Bi-Objective Diversity Problem

2018

Abstract The Max-Sum diversity and the Max-Min diversity are two well-known optimization models to capture the notion of selecting a subset of diverse points from a given set. The resolution of their associated optimization problems provides solutions of different structures, in both cases with desirable characteristics. They have been extensively studied and we can find many metaheuristic methodologies, such as Greedy Randomized Adaptive Search Procedure, Tabu Search, Iterated Greedy, Variable Neighborhood Search, and Genetic algorithms applied to them to obtain high quality solutions. In this paper we solve the bi-objective problem in which both models are simultaneously optimized. No pre…

Mathematical optimization021103 operations researchOptimization problemComputer science0211 other engineering and technologiesGeneral Engineering02 engineering and technologyResolution (logic)Tabu searchComputer Science ApplicationsSet (abstract data type)Artificial IntelligenceGenetic algorithm0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingHeuristicsMetaheuristicVariable neighborhood searchGreedy randomized adaptive search procedureExpert Systems with Applications
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The stacker crane problem and the directed general routing problem

2015

[EN] This article deals with the polyhedral description and the resolution of the directed general routing problem (DGRP) and the stacker crane problem (SCP). The DGRP contains a large number of important arc and node routing problems as special cases, including the SCP. Large families of facet-defining inequalities for the DGRP are described and a branch-and-cut algorithm for these problems is presented. Extensive computational experiments over different sets of DGRP and SCP instances are included.

Mathematical optimizationDirected general routing problemStacker crane problemComputer Networks and CommunicationsStackerNode (networking)Branch-and-cut algorithmDirected graphResolution (logic)Directed rural postman problemHardware and ArchitectureRouting (electronic design automation)MATEMATICA APLICADASoftwareInformation SystemsMathematics
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Conflict resolution in the multi-stakeholder stepped spillway design under uncertainty by machine learning techniques

2021

Abstract The optimal spillway design is of great significance since these structures can reduce erosion downstream of the dams. This study proposes a risk-based optimization framework for a stepped spillway to achieve an economical design scenario with the minimum loss in hydraulic performance. Accordingly, the stepped spillway was simulated in the FLOW-3D® model, and the validated model was repeatedly performed for various geometric states. The results were used to form a Multilayer Perceptron artificial neural network (MLP-ANN) surrogate model. Then, a risk-based optimization model was formed by coupling the MLP-ANN and NSGA-II. The concept of conditional value at risk (CVaR) was utilized…

Mathematical optimizationExpected shortfallSpillwaySurrogate modelArtificial neural networkComputer scienceCVARMultilayer perceptronConflict resolutionStepped spillwayVDP::Technology: 500::Information and communication technology: 550SoftwareApplied Soft Computing
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Geometric constraint solving: The witness configuration method

2006

Geometric constraint solving is a key issue in CAD, CAM and PLM. The systems of geometric constraints are today studied and decomposed with graph-based methods, before their numerical resolution. However, graph-based methods can detect only the simplest (called structural) dependences between constraints; they cannot detect subtle dependences due to theorems. To overcome these limitations, this paper proposes a new method: the system is studied (with linear algebra tools) at a witness configuration, which is intuitively similar to the unknown one, and easy to compute.

Mathematical optimizationNumerical resolutionLinear algebraGraph (abstract data type)CADRigidity theoryComputer Graphics and Computer-Aided DesignAlgorithmWitnessIndustrial and Manufacturing EngineeringComputer Science ApplicationsMathematicsComputer-Aided Design
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MCR-ALS on metabolic networks: Obtaining more meaningful pathways

2015

[EN] With the aim of understanding the flux distributions across a metabolic network, i.e. within living cells, Principal Component Analysis (PCA) has been proposed to obtain a set of orthogonal components (pathways) capturing most of the variance in the flux data. The problems with this method are (i) that no additional information can be included in the model, and (ii) that orthogonality imposes a hard constraint, not always reasonably. To overcome these drawbacks, here we propose to use a more flexible approach such as Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) to obtain this set of biological pathways through the network. By using this method, different constraint…

Mathematical optimizationProcess Chemistry and TechnologyESTADISTICA E INVESTIGACION OPERATIVAMetabolic networkMetabolic networkLeast SquaresVariance (accounting)Least squaresINGENIERIA DE SISTEMAS Y AUTOMATICAComputer Science ApplicationsAnalytical ChemistrySet (abstract data type)Constraint (information theory)OrthogonalityPichia pastorisPrincipal component analysisA priori and a posterioriMultivariate Curve Resolution-AlternatingGrey modellingSpectroscopySoftwareMathematics
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Simulated one-pass list-mode: an approach to on-the-fly system matrix calculation.

2013

In the development of prototype systems for positron emission tomography a valid and robust image reconstruction algorithm is required. However, prototypes often employ novel detector and system geometries which may change rapidly under optimization. In addition, developing systems generally produce highly granular, or possibly continuous detection domains which require some level of on-the-fly calculation for retention of measurement precision. In this investigation a new method of on-the-fly system matrix calculation is proposed that provides advantages in application to such list-mode systems in terms of flexibility in system modeling. The new method is easily adaptable to complicated sy…

Mathematical optimizationRadiological and Ultrasound Technology010308 nuclear & particles physicsRandom number generationDetectorProcess (computing)Iterative reconstructionMaximizationSystems modelingModels Theoretical01 natural sciences030218 nuclear medicine & medical imaging03 medical and health sciencesNoise0302 clinical medicinePositron-Emission Tomography0103 physical sciencesImage Processing Computer-AssistedRadiology Nuclear Medicine and imagingAlgorithmImage resolutionMathematicsPhysics in medicine and biology
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Methods cooperation for multiresolution motion estimation

2002

For a medical application, we are interested in an estimation of optical flow on a patient's face, particularly around the eyes. Among the methods of optical flow estimation, gradient estimation and block matching are the main methods. However, the gradient-based approach can only be applied for small displacements (one or two pixels). Gener- ally, the process of block matching leads to good results only if the searching strategy is judiciously selected. Our approach is based on a Markov random field model, combined with an algorithm of block match- ing in a multiresolution scheme. The multiresolution approach allows de- tection of a large range of speeds. The large displacements are detect…

Mathematical optimizationRandom fieldMarkov random fieldMarkov chainComputer scienceGeneral EngineeringOptical flowInitializationMotion detectionImage processingAtomic and Molecular Physics and OpticsOptical flow estimationMotion estimationImage resolutionAlgorithmBlock (data storage)Block-matching algorithmOptical Engineering
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Linear Programming Based Methods for Solving Arc Routing Problems

2000

From the pioneering works of Dantzig, Edmonds and others, polyhedral (i.e. linear programming based) methods have been successfully applied to the resolution of many combinatorial optimization problems. See Junger, Reinelt & Rinaldi (1995) for an excellent survey on this topic. Roughly speaking, the method consists of trying to formulate the problem as a Linear Program and using the existing powerful methods of Linear Programming to solve it.

Mathematical optimizationRoute inspection problemLinear programmingComputer scienceCombinatorial optimization problemResolution (logic)Arc routing
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A hybrid genetic algorithm with local search: I. Discrete variables: optimisation of complementary mobile phases

2001

Abstract A hybrid genetic algorithm was developed for a combinatorial optimisation problem. The assayed hybridation modifies the reproduction pattern of the genetic algorithm through the application of a local search method, which enhances each individual in each generation. The method is applied to the optimisation of the mobile phase composition in liquid chromatography, using two or more mobile phases of complementary behaviour. Each of these phases concerns the optimal separation of certain compounds in the analysed mixture, while the others can remain overlapped. This optimisation approach may be useful in situations where full resolution with a single mobile phase is unfeasible. The o…

Mathematical optimizationbusiness.industryProcess Chemistry and TechnologyComputationBinary numberResolution (logic)Computer Science ApplicationsAnalytical ChemistryEncoding (memory)Genetic algorithmMemetic algorithmCombinatorial searchLocal search (optimization)businessAlgorithmSpectroscopySoftwareMathematicsChemometrics and Intelligent Laboratory Systems
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Best Proximity Points for Some Classes of Proximal Contractions

2013

Given a self-mapping g: A → A and a non-self-mapping T: A → B, the aim of this work is to provide sufficient conditions for the existence of a unique point x ∈ A, called g-best proximity point, which satisfies d g x, T x = d A, B. In so doing, we provide a useful answer for the resolution of the nonlinear programming problem of globally minimizing the real valued function x → d g x, T x, thereby getting an optimal approximate solution to the equation T x = g x. An iterative algorithm is also presented to compute a solution of such problems. Our results generalize a result due to Rhoades (2001) and hence such results provide an extension of Banach's contraction principle to the case of non-s…

Mathematical optimizationmetric spacesArticle SubjectIterative methodApplied Mathematicslcsh:MathematicsWork (physics)proximal contractionbest proximity pointExtension (predicate logic)Resolution (logic)lcsh:QA1-939Nonlinear programmingReal-valued functionPoint (geometry)Settore MAT/03 - GeometriaContraction principleAnalysisMathematicsAbstract and Applied Analysis
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