Search results for "Mathematical optimization"

showing 10 items of 1300 documents

Multiobjective ant colony search algorithm optimal electrical distribution system planning

2005

A dynamic multiobjective, MO, algorithm based on the ant colony search, the multiobjective ant colony search algorithm, MOACS, is presented. The application domain is that of dynamic planning for electrical distribution systems. A time horizon of H years has been considered during which the distribution system are modified according to the new internal (loads) and external (market, reliability, power quality) requirements. In this scenario, the objectives the Authors consider most important for utilities in strategical planning are: the quality requirement connected to the decrease of the expected number of interruptions per year and customer, in the considered time frame, and the choice fo…

Mathematical optimizationSearch algorithmComputer scienceReliability (computer networking)Ant colony optimization algorithmsmedia_common.quotation_subjectMathematicsofComputing_NUMERICALANALYSISPareto principleQuality (business)Time horizonAnt colonyComputingMethodologies_ARTIFICIALINTELLIGENCEmedia_commonProceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)
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Fuzzified Game Tree Search – Precision vs Speed

2012

Most game tree search algorithms consider finding the optimal move. That is, given an evaluation function they guarantee that selected move will be the best according to it. However, in practice most evaluation functions are themselves approximations and cannot be considered "optimal". Besides, we might be satisfied with nearly optimal solution if it gives us a considerable performance improvement. In this paper we present the approximation based implementations of the fuzzified game tree search algorithm. The paradigm of the algorithm allows us to efficiently find nearly optimal solutions so we can choose the "target quality" of the search with arbitrary precision --- either it is 100% (pr…

Mathematical optimizationSearch algorithmMonte Carlo tree searchBeam searchBest-first searchPerformance improvementEvaluation functionAlpha–beta pruningIterative deepening depth-first searchAlgorithmMathematics
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Large multiple neighborhood search for the clustered vehicle-routing problem

2018

Abstract The clustered vehicle-routing problem is a variant of the classical capacitated vehicle-routing problem in which customers are partitioned into clusters, and it is assumed that each cluster must have been served completely before the next cluster is served. This decomposes the problem into three subproblems, i.e., the assignment of clusters to routes, the routing inside each cluster, and the sequencing of the clusters in the routes. The second task requires the solution of several Hamiltonian path problems, one for each possibility to route through the cluster. We pre-compute the Hamiltonian paths for every pair of customers of each cluster. We present a large multiple neighborhood…

Mathematical optimizationSequence021103 operations researchInformation Systems and ManagementGeneral Computer ScienceGeneralization0211 other engineering and technologies02 engineering and technologyManagement Science and Operations ResearchHamiltonian pathIndustrial and Manufacturing EngineeringTask (computing)symbols.namesakeComputingMethodologies_PATTERNRECOGNITIONModeling and SimulationVehicle routing problem0202 electrical engineering electronic engineering information engineeringsymbolsCluster (physics)020201 artificial intelligence & image processingRouting (electronic design automation)Hamiltonian (control theory)MathematicsEuropean Journal of Operational Research
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Optimal selection of the four best of a sequence

1993

We consider the situation in which the decision-maker is allowed to have four choices with purpose to choose exactly the four absolute best candidates fromN applicants. The optimal stopping rule and the maximum probability of making the right choice are given for largeN∈N, the maximum asymptotic value of the best choice being limN→∞P(win)≈0.12706.

Mathematical optimizationSequenceGeneral MathematicsValue (economics)Stopping ruleOptimal stopping ruleOptimal stoppingManagement Science and Operations ResearchMathematical economicsSoftwareSelection (genetic algorithm)Secretary problemMathematicsZOR Zeitschrift f� Operations Research Methods and Models of Operations Research
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A bilateral convergent bounding technique for plastic deformations

1990

For the class of elastic perfectly plastic discrete structures, subjected to a dynamic loading history, a bilateral bounding technique for plastic deformations has been studied. The computation of the bound is founded on the concept that to obtain it, any history of fictitious plastic deformations can be used, if only admissible. Such history is obtained by solving a sequence of linear programming problems (LPPs) with a multiple step compared to the step of the sequence of the quadratic programming problems (QPPs) adopting in the classic elasto-plastic analysis. The constraints of the LPPs coincide with the constraints of the QPPs, while the objective function is a linear combination of var…

Mathematical optimizationSequenceLinear programmingMechanics of MaterialsBounding overwatchDynamic loadingMechanical EngineeringComputationApplied mathematicsQuadratic programmingCondensed Matter PhysicsLinear combinationMathematicsMeccanica
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Efficient solution of the first passage problem by Path Integration for normal and Poissonian white noise

2015

Abstract In this paper the first passage problem is examined for linear and nonlinear systems driven by Poissonian and normal white noise input. The problem is handled step-by-step accounting for the Markov properties of the response process and then by Chapman–Kolmogorov equation. The final formulation consists just of a sequence of matrix–vector multiplications giving the reliability density function at any time instant. Comparison with Monte Carlo simulation reveals the excellent accuracy of the proposed method.

Mathematical optimizationSequenceMarkov chainPoisson proceMechanical EngineeringReliability (computer networking)Monte Carlo methodAerospace EngineeringOcean EngineeringStatistical and Nonlinear PhysicsProbability density functionWhite noiseWhite noiseCondensed Matter PhysicsPath IntegrationNonlinear systemNuclear Energy and EngineeringStructural reliabilityApplied mathematicsFirst passage problemRandom vibrationSettore ICAR/08 - Scienza Delle CostruzioniRandom vibrationCivil and Structural EngineeringMathematicsProbabilistic Engineering Mechanics
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A comparison of column-generation approaches to the Synchronized Pickup and Delivery Problem

2015

Abstract In the Synchronized Pickup and Delivery Problem (SPDP), user-specified transportation requests from origin to destination points have to be serviced by a fleet of homogeneous vehicles. The task is to find a set of minimum-cost routes satisfying pairing and precedence, capacities, and time windows. Additionally, temporal synchronization constraints couple the service times at the pickup and delivery locations of the customer requests in the following way: a request has to be delivered within prespecified minimum and maximum time lags (called ride times) after it has been picked up. The presence of these ride-time constraints severely complicates the subproblem of the natural column-…

Mathematical optimizationService (systems architecture)Information Systems and ManagementGeneral Computer ScienceComputer scienceManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringSet (abstract data type)Task (computing)Modeling and SimulationVehicle routing problemPickupColumn generationInteger (computer science)European Journal of Operational Research
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Revenue-based adaptive deficit round robin

2005

This paper presents an adaptive resource allocation model that is based on the DRR queuing policy. The model ensures QoS requirements and tries to maximize a service provider's revenue by manipulating quantum values of the DRR scheduler. To calculate quantum values, it is proposed to use the revenue criterion that controls the allocation of free resources. The simulation considers a single node with the implemented model that serves several service classes with different QoS requirements and traffic characteristics. It is shown that the total revenue can be increased due to the allocation of unused resources to more expensive service classes. At the same time, bandwidth and delay guarantees…

Mathematical optimizationService qualityQueueing theoryComputer scienceresource allocation modelQuality of serviceTotal revenueQoSDeficit round robinService providerComputer securitycomputer.software_genreScheduling (computing)DRR queuingRevenueResource allocationcomputerQueue
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New analytical approach to analyze the nonlinear regime of stochastic resonance

2015

We propose some approximate methods to explore the nonlinear regime of the stochastic resonance phenomenon. These approximations correspond to different truncation schemes of cumulants. We compare the theoretical results for the signal power amplification, obtained by using ordinary cumulant truncation schemes, that is Gaussian and excess approximations, the modified two-state approximation with those obtained by numerical simulations of the Langevin equation describing the dynamics of the system.

Mathematical optimizationSettore FIS/02 - Fisica Teorica Modelli E Metodi MatematiciCumulant truncation scheme; modified two-state approximation; nonlinear regime; signal power amplification; stochastic resonance phenomenon; Electrical and Electronic Engineering; Acoustics and UltrasonicsCumulant truncation schemeAcoustics and UltrasonicsTruncationStochastic resonanceGaussianSignalPower (physics)Langevin equationsymbols.namesakeNonlinear systemstochastic resonance phenomenonsymbolsStatistical physicssignal power amplificationElectrical and Electronic Engineeringmodified two-state approximationnonlinear regimeCumulantMathematics
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Global sensitivity analysis in wastewater treatment modelling

2019

Global sensitivity analysis (GSA) is a valuable tool to support the use of mathematical models. GSA allows the identifcation of the effect of model and input factor uncertainty on the model response, also considering the effect due to the interactions among factors. During recent years, the wastewater modelling feld has embraced the use of GSA. Wastewater modellers have tried to transfer the knowledge and experience from other disciplines and other water modelling felds.

Mathematical optimizationSettore ICAR/03 - Ingegneria Sanitaria-AmbientaleComputational burden convergence modelling numerical methods sensitivity analysis water modellingGlobal sensitivity analysisNumerical analysisConvergence (routing)Sewage treatmentMathematics
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