Search results for "nonlinear programming"

showing 10 items of 31 documents

PAINT–SiCon: constructing consistent parametric representations of Pareto sets in nonconvex multiobjective optimization

2014

We introduce a novel approximation method for multiobjective optimization problems called PAINT–SiCon. The method can construct consistent parametric representations of Pareto sets, especially for nonconvex problems, by interpolating between nondominated solutions of a given sampling both in the decision and objective space. The proposed method is especially advantageous in computationally expensive cases, since the parametric representation of the Pareto set can be used as an inexpensive surrogate for the original problem during the decision making process. peerReviewed

Mathematical optimizationControl and OptimizationApplied MathematicsMathematicsofComputing_NUMERICALANALYSISPareto principleSampling (statistics)Management Science and Operations ResearchSpace (mathematics)Multi-objective optimizationComputer Science ApplicationsNonlinear programmingSet (abstract data type)piecewise linear approximationmultiple criteria programmingnonlinear programmingRepresentation (mathematics)Parametric statisticsMathematicsJournal of Global Optimization
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Synchronous approach in interactive multiobjective optimization

2006

We introduce a new approach in the methodology development for interactive multiobjective optimization. The presentation is given in the context of the interactive NIMBUS method, where the solution process is based on the classification of objective functions. The idea is to formulate several scalarizing functions, all using the same preference information of the decision maker. Thus, opposed to fixing one scalarizing function (as is done in most methods), we utilize several scalarizing functions in a synchronous way. This means that we as method developers do not make the choice between different scalarizing functions but calculate the results of different scalarizing functions and leave t…

Mathematical optimizationInformation Systems and ManagementGeneral Computer ScienceComputer sciencebusiness.industrymedia_common.quotation_subjectContext (language use)Management Science and Operations ResearchMultiple-criteria decision analysisMulti-objective optimizationIndustrial and Manufacturing EngineeringNonlinear programmingNonlinear systemModeling and SimulationSoftware systemArtificial intelligenceFunction (engineering)businessmedia_commonEuropean Journal of Operational Research
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A spreadsheet modeling approach to the Holt–Winters optimal forecasting

2001

Abstract The objective of this paper is to determine the optimal forecasting for the Holt–Winters exponential smoothing model using spreadsheet modeling. This forecasting procedure is especially useful for short-term forecasts for series of sales data or levels of demand for goods. The non-linear programming problem associated with this forecasting model is formulated and a spreadsheet model is used to solve the problem of optimization efficiently. Also, a spreadsheet makes it possible to work in parallel with various objective functions (measures of forecast errors) and different procedures for calculating the initial values of the components of the model. Using a scenario analysis, the se…

Mathematical optimizationInformation Systems and ManagementGeneral Computer ScienceSeries (mathematics)Computer scienceExponential smoothingManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringNonlinear programmingMaxima and minimaSet (abstract data type)Order (business)Modeling and SimulationScenario analysisPhysics::Atmospheric and Oceanic PhysicsEuropean Journal of Operational Research
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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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Scatter Search and Path Relinking: Advances and Applications

2006

Scatter search (SS) is a population-based method that has recently been shown to yield promising outcomes for solving combinatorial and nonlinear optimization problems. Based on formulations originally proposed in the 1960s for combining decision rules and problem constraints, SS uses strategies for combining solution vectors that have proved effective in a variety of problem settings. Path relinking (PR) has been suggested as an approach to integrate intensification and diversification strategies in a search scheme. The approach may be viewed as an extreme (highly focused) instance of a strategy that seeks to incorporate attributes of high quality solutions, by creating inducements to favo…

Mathematical optimizationeducation.field_of_studyEngineeringbusiness.industryPopulationDecision ruleTabu searchNonlinear programmingVariety (cybernetics)Path (graph theory)Local search (optimization)Set (psychology)educationbusiness
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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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Interactive Nonlinear Multiobjective Procedures

2006

An overview of the interactive methods for solving nonlinear multiple criteria decision making problems is given. In interactive methods, the decision maker progressively provides preference information so that the most satisfactory compromise can be found. The basic features of several methods are introduced and some theoretical results are provided. In addition, references to modifications and applications as well as to other methods are indicated.

Nonlinear systemMathematical optimizationComputer scienceCompromisemedia_common.quotation_subjectMultiple criteriaDecision makerMulti-objective optimizationPreferenceNonlinear programmingmedia_common
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Some Methods for Nonlinear Multi-objective Optimization

2001

A general overview of nonlinear multiobjective optimization methods is given. The basic features of several methods are introduced so that an appropriate method could be found for different purposes. The methods are classified according to the role of a decision maker in the solution process. The main emphasis is devoted to interactive methods where the decision maker progressively provides preference information so that the most satisfactory solution can be found.

Nonlinear systemMathematical optimizationComputer scienceMulti-objective optimizationPreferenceNonlinear programming
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Distributed Resource Allocation for Energy Efficiency in OFDMA Multicell Networks with Wireless Power Transfer

2019

In this paper, an energy-efficient resource allocation problem is investigated for the wireless power transfer (WPT)-enabled OFDMA multicell networks. In the considered system, multiple base stations (BSs) with a large number of antennas are responsible to provide WPT in the downlink, and the users can recycle and utilize the received energy for uplink data transmission. The role of BS is to execute WPT; thus, there are no data transmissions in the downlink. A time-division protocol is considered to divide the time of downlink WPT and uplink wireless information transfer into separate time slots. With the objective to improve the energy efficiency, we propose the time, subcarrier, and power…

Optimization problemComputer Networks and CommunicationsComputer sciencesubcarrier allocationenergiatehokkuusDistributed computingwireless power transfer02 engineering and technologyData_CODINGANDINFORMATIONTHEORYSubcarrierNonlinear programmingantenna selectionBase stationTelecommunications link0202 electrical engineering electronic engineering information engineeringComputer Science::Networking and Internet ArchitectureWirelessElectrical and Electronic Engineeringvoimansiirtoenergy efficiencyComputer Science::Information Theoryta213business.industryComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKStime allocation020206 networking & telecommunicationspower allocationChannel state informationResource allocationbusinesslangattomat verkotEfficient energy use
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Interactive Nonlinear Multiobjective Optimization Methods

2016

An overview of interactive methods for solving nonlinear multiobjective optimization problems is given. In interactive methods, the decision maker progressively provides preference information so that the most satisfactory Pareto optimal solution can be found for her or his. The basic features of several methods are introduced and some theoretical results are provided. In addition, references to modifications and applications as well as to other methods are indicated. As the role of the decision maker is very important in interactive methods, methods presented are classified according to the type of preference information that the decision maker is assumed to provide. peerReviewed

Pareto optimalityMathematical optimization021103 operations researchComputer sciencemultiple criteria decision making0211 other engineering and technologies02 engineering and technologyinteractive methodsDecision makernonlinear optimizationMulti-objective optimizationPreferenceNonlinear programmingPareto optimalNonlinear systemMultiobjective optimization problemmultiple objectives0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing
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