Search results for "Mathematical optimization"

showing 10 items of 1300 documents

Density flow over networks: A mean-field game theoretic approach

2014

A distributed routing control algorithm for dynamic networks has recently been presented in the literature. The networks were modeled using time evolution of density at network edges and the routing control algorithm allowed edge density to converge to a Wardrop equilibrium, which was characterized by an equal traffic density on all used paths. We borrow the idea and rearrange the density model to recast the problem within the framework of mean-field games. The contribution of this paper is three-fold. First, we provide a mean-field game formulation of the problem at hand. Second, we illustrate an extended state space solution approach. Third, we study the stochastic case where the density …

game theoryMathematical optimizationDensity flowDensity modelTime evolutionMean field gameSettore ING-INF/04 - Automaticamean field gameState spaceSettore MAT/09 - Ricerca OperativaRouting (electronic design automation)Density evolutionBrownian motionMathematics53rd IEEE Conference on Decision and Control
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Coupling dynamic simulation and interactive multiobjective optimization for complex problems: An APROS-NIMBUS case study

2014

Dynamic process simulators for plant-wide process simulation and multiobjective optimization tools can be used by industries as a means to cut costs and enhance profitability. Specifically, dynamic process simulators are useful in the process plant design phase, as they provide several benefits such as savings in time and costs. On the other hand, multiobjective optimization tools are useful in obtaining the best possible process designs when multiple conflicting objectives are to be optimized simultaneously. Here we concentrate on interactive multiobjective optimization. When multiobjective optimization methods are used in process design, they need an access to dynamic process simulators, …

implementation challengesMathematical optimizationOptimization problemProcess (engineering)Computer scienceta111General Engineeringaugmented interactive multiobjective optimization algorithminteractive methodMulti-objective optimizationComputer Science ApplicationsEngineering optimizationSeparation processDynamic simulationSimulation-based optimizationIND-NIMBUSArtificial Intelligencedynamic process simulationApache ThriftPareto optimal solutionsProcess simulationsimulation based optimizationExpert Systems with Applications
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Hybridizing large neighborhood search and exact methods for generalized vehicle routing problems with time windows

2021

International audience; Delivery options are at the heart of the generalized vehicle routing problem with time windows (GVRPTW) allowing that customer requests are shipped to alternative delivery locations which can also have different time windows. Recently, the vehicle routing problem with delivery options was introduced into the scientific literature. It extends the GVRPTW by capacities of shared locations and by specifying service-level constraints defined by the customers' preferences for delivery options. The vehicle routing problem with delivery options also generalizes the vehicle routing problem with home roaming delivery locations and the vehicle routing problem with multiple time…

large neighborhood searchtime windowsMathematical optimizationComputer science030503 health policy & services05 social sciences050109 social psychologyTransportation[INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO]Management Science and Operations ResearchSpace (commercial competition)03 medical and health sciencesmatheuristicTime windowsModeling and SimulationVehicle routing problemBenchmark (computing)Large neighborhood search0501 psychology and cognitive sciencesRoamingLayer (object-oriented design)0305 other medical scienceFocus (optics)vehicle routingdelivery optionsEURO Journal on Transportation and Logistics
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A visualization technique for accessing solution pool in interactive methods of multiobjective optimization

2015

<pre>Interactive methods of <span>multiobjective</span> optimization repetitively derive <span>Pareto</span> optimal solutions based on decision maker's preference information and present the obtained solutions for his/her consideration. Some interactive methods save the obtained solutions into a solution pool and, at each iteration, allow the decision maker considering any of solutions obtained earlier. This feature contributes to the flexibility of exploring the <span>Pareto</span> optimal set and learning about the optimization problem. However, in the case of many objective functions, the accumulation of derived solutions makes accessing the sol…

multidimensional scalingMathematical optimizationOptimization problemComputer Networks and CommunicationsComputer sciencevisualisointiPareto front visualizationcomputer.software_genreMulti-objective optimizationSet (abstract data type)menetelmätMultidimensional scalingMultiobjective optimizationdimensionality reductionFlexibility (engineering)pareto-tehokkuusDimensionality reductionMultiobjective optimization ; interactive methods ; Pareto front visualization ; dimensionality reduction ; multidimensional scalinginteractive methodsNIMBUSmonitavoiteoptimointiComputer Science ApplicationsVisualizationComputational Theory and MathematicsFeature (computer vision)interaktiivisuusData miningcomputer
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Energy efficient resource allocation in heterogeneous software defined network: A reverse combinatorial auction approach

2015

In this paper, resource allocation for energy effi- ciency in heterogeneous Software Defined Network (SDN) with multiple network service providers (NSPs) is studied. The considered problem is modeled as a reverse combinatorial auction game, which takes different quality of service (QoS) requirements into account. The heterogeneous network selection associated with power allocation problem is optimized by maximizing the energy efficiency of data transmission. By exploiting the properties of fractional programming, the resulting non-convex Winner Determination Problem (WDP) is transformed into an equivalent subtractive convex optimization problem. The proposed reverse combinatorial auction ga…

network service providersComputer Science::Computer Science and Game TheoryMathematical optimizationenergiatehokkuusComputer scienceDistributed computingQuality of serviceSoftware Defined NetworksAuction algorithmSDNCombinatorial auctionResource allocationSoftware-defined networkingHeterogeneous networkEfficient energy use2015 IEEE/CIC International Conference on Communications in China (ICCC)
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Water distribution network robust design based on energy surplus index maximization

2015

The aim of this paper is to show that energy surplus indices, such as resilience index, besides providing a very good indirect measure of water distribution network reliability to be adopted during the design phase, represent also a valuable and effective indicator of the robustness of the network in alternative network scenarios, and can thus be profitably used in condition of future demands uncertainty. The methodology adopted consisted of (I) multi-objective design optimization performed in order to minimize construction costs while maximizing the resilience index; (II) retrospective performance assessment of the alternative solutions of the Pareto front obtained, under demand conditions…

optimal robust designEngineeringTopological complexityMathematical optimizationenergy surplus indexDistribution networksManagement sciencebusiness.industrySettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaMaximizationWater distribution networkMulti-objective optimizationwater distribution networks energy surplus indexNONetwork planning and designRobust designwater distribution networksRobustness (computer science)resilience indexResilience indexbusinessWater Science and TechnologyWater Supply
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Surrogate-assisted multicriteria optimization: Complexities, prospective solutions, and business case

2017

Complexity in solving real-world multicriteria optimization problems often stems from the fact that complex, expensive, and/or time-consuming simulation tools or physical experiments are used to evaluate solutions to a problem. In such settings, it is common to use efficient computational models, often known as surrogates or metamodels, to approximate the outcome (objective or constraint function value) of a simulation or physical experiment. The presence of multiple objective functions poses an additional layer of complexity for surrogate-assisted optimization. For example, complexities may relate to the appropriate selection of metamodels for the individual objective functions, extensive …

optimization problemsMathematical optimizationComputer scienceStrategy and Managementmedia_common.quotation_subjectConstraint (computer-aided design)0211 other engineering and technologiesmultiple criteria decision makingGeneral Decision Sciences02 engineering and technologyMulti-objective optimizationOutcome (game theory)evolutionary multicriteria optimizationEngineering optimizationmulticriteria optimization0202 electrical engineering electronic engineering information engineeringPoint (geometry)Business caseFunction (engineering)media_commonta113Computational model021103 operations researchmetamodelsexpensive optimization problemssurrogatesexpensesmachine learning020201 artificial intelligence & image processing
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The fractional Calderón problem: Low regularity and stability

2017

The Calder\'on problem for the fractional Schr\"odinger equation was introduced in the work \cite{GSU}, which gave a global uniqueness result also in the partial data case. This article improves this result in two ways. First, we prove a quantitative uniqueness result showing that this inverse problem enjoys logarithmic stability under suitable a priori bounds. Second, we show that the results are valid for potentials in scale-invariant $L^p$ or negative order Sobolev spaces. A key point is a quantitative approximation property for solutions of fractional equations, obtained by combining a careful propagation of smallness analysis for the Caffarelli-Silvestre extension and a duality argumen…

osittaisdifferentiaaliyhtälötMathematical optimizationCaldernón problemLogarithmApproximation propertyApplied Mathematics010102 general mathematicsDuality (optimization)stabilityInverse problem01 natural sciencesStability (probability)inversio-ongelmatSchrödinger equation010101 applied mathematicsSobolev spacesymbols.namesakeMathematics - Analysis of PDEssymbolsApplied mathematicsfractional LaplacianUniqueness0101 mathematicsAnalysisMathematicsNonlinear Analysis
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Enhanced chain dynamics in loop-sorting-systems by means of layout optimization and a kinematic model of the polygon action

2012

Published version of an article in the journal: Structural and Multidisciplinary Optimization. Also available from the publisher at: http://dx.doi.org/10.1007/s00158-011-0743-7 Poor dynamics owing to polygon action is a known concern in mechanical applications of closed articulated chains. In this paper a kinematic model of the polygon action in large chains of loop-sorting-systems is proposed. Through optimization techniques the chain dynamics is improved by minimizing the polygon action using a parametric model of the track layout as design variables. Three formulations of the kinematic polygon action are tested on an average sized planer tracks layout to find a superior model. Verificati…

polygon actionLoop (graph theory)Mathematical optimizationControl and OptimizationComputer scienceengineeringVDP::Technology: 500::Mechanical engineering: 570SortingKinematicsloop-sorting-systemsComputer Graphics and Computer-Aided DesignAction (physics)Computer Science Applicationsmulti-body dynamicsChain (algebraic topology)Control and Systems EngineeringParametric modelPolygonEngineering design processAlgorithmoptimizationSoftware
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Scheduling under the network of temporo-spatial proximity relationships

2017

We discuss and introduce to the schedulingeld a novel, qualitative optimization model - scheduling under the network of temporo-spatial proximity relationships.We introduce a half perimeter proximity measure as an objective of scheduling.We present and evaluate an incremental Sequence Pair neighborhood evaluation algorithm, applicable to both scheduling and rectangle packing problems in VLSI industry. In this paper, we discuss and introduce to the scheduling field a novel optimization objective - half perimeter proximity measure in scheduling under the network of temporo-spatial proximity relationships. The presented approach enables to qualitatively express various reasons of scheduling ce…

proximity relationshipsMathematical optimizationGeneral Computer Sciencerectangle packing problemEvaluation algorithm0102 computer and information sciences02 engineering and technologyIntegrated circuitManagement Science and Operations Research01 natural scienceslaw.inventionScheduling (computing)lawApproximation error0202 electrical engineering electronic engineering information engineeringschedulingComputer Science::Operating SystemsMathematicsVery-large-scale integrationProximity measureneighborhood evaluation010201 computation theory & mathematicsModeling and Simulation020201 artificial intelligence & image processingsequence pairRectangle packingComputers & Operations Research
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