Search results for "Criteria"

showing 10 items of 582 documents

Interactive Multiobjective Robust Optimization with NIMBUS

2018

In this paper, we introduce the MuRO-NIMBUS method for solving multiobjective optimization problems with uncertain parameters. The concept of set-based minmax robust Pareto optimality is utilized to tackle the uncertainty in the problems. We separate the solution process into two stages: the pre-decision making stage and the decision making stage. We consider the decision maker’s preferences in the nominal case, i.e., with the most typical or undisturbed values of the uncertain parameters. At the same time, the decision maker is informed about the objective function values in the worst case to support her/him to make an informed decision. To help the decision maker to understand the behavio…

Mathematical optimization021103 operations researchComputer sciencepareto-tehokkuuspäätöksenteko0211 other engineering and technologiesPareto principlemultiple criteria decision makingRobust optimization02 engineering and technologyrobustnessinteractive methodsDecision makerMinimaxTwo stagesrobust Pareto optimalitymonitavoiteoptimointiepävarmuusMultiobjective optimization problemRobustness (computer science)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing
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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
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NAUTILUS Navigator : free search interactive multiobjective optimization without trading-off

2019

We propose a novel combination of an interactive multiobjective navigation method and a trade-off free way of asking and presenting preference information. The NAUTILUS Navigator is a method that enables the decision maker (DM) to navigate in real time from an inferior solution to the most preferred solution by gaining in all objectives simultaneously as (s)he approaches the Pareto optimal front. This means that, while the DM reaches her/his most preferred solution, (s)he avoids anchoring around the starting solution and, at the same time, sees how the ranges of the reachable objective function values shrink without trading-off. The progress of the motion towards the Pareto optimal front is…

Mathematical optimizationControl and Optimization0211 other engineering and technologiesAnchoringpäätöksentukijärjestelmät02 engineering and technologyManagement Science and Operations ResearchMulti-objective optimizationMotion (physics)Set (abstract data type)käyttöliittymätPreference (economics)MathematicsGraphical user interface021103 operations researchbusiness.industryApplied Mathematicsgraphical user interfaceFunction (mathematics)interactive methodsDecision makermonitavoiteoptimointiComputer Science Applicationsnavigointiinteraktiivisuusmulticriteria decision makingbusinesstrade-off free
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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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A survey on handling computationally expensive multiobjective optimization problems using surrogates: non-nature inspired methods

2015

Computationally expensive multiobjective optimization problems arise, e.g. in many engineering applications, where several conflicting objectives are to be optimized simultaneously while satisfying constraints. In many cases, the lack of explicit mathematical formulas of the objectives and constraints may necessitate conducting computationally expensive and time-consuming experiments and/or simulations. As another challenge, these problems may have either convex or nonconvex or even disconnected Pareto frontier consisting of Pareto optimal solutions. Because of the existence of many such solutions, typically, a decision maker is required to select the most preferred one. In order to deal wi…

Mathematical optimizationEngineeringControl and Optimizationbusiness.industryPareto principlePareto frontierDecision makerSampling techniqueComputer Graphics and Computer-Aided DesignMulti-objective optimizationComputer Science ApplicationsMultiobjective optimization problemPareto optimalConflicting objectivesBlack-box functionControl and Systems EngineeringMulticriteria Decision Making (MCDM)Computational costNature inspiredMetamodeling techniquebusinessEngineering design processSoftwareStructural and Multidisciplinary 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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Using box indices in supporting comparison in multiobjective optimization

2009

Because of the conflicting nature of criteria or objectives, solving a multiobjective optimization problem typically requires interaction with a decision maker who can specify preference information related to the objectives in the problem in question. Due to the difficulties of dealing with multiple objectives, the way information is presented plays a very important role. Questions posed to the decision maker must be simple enough and information shown must be easy to understand. For this purpose, visualization and graphical representations can be useful and constitute one of the main tools used in the literature. In this paper, we propose to use box indices to represent information relate…

Mathematical optimizationInformation Systems and ManagementGeneral Computer Sciencebusiness.industryScale (chemistry)Information and Computer ScienceManagement Science and Operations ResearchMachine learningcomputer.software_genreMultiple-criteria decision analysisMulti-objective optimizationIndustrial and Manufacturing EngineeringPreferenceVisualizationSimple (abstract algebra)Modeling and SimulationArtificial intelligenceGraphicsbusinesscomputerMathematicsEuropean Journal of Operational Research
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SMAA-TRI

2007

ELECTRE TRI is a multiple criteria decision aiding sorting method with a history of successful real-life applications. In ELECTRE TRI, values for certain parameters, such as criteria weights, thresholds, category profiles, and lambda cutting level, have to be provided. We propose a new method, SMAA-TRI, that is based on Stochastic Multicriteria Acceptability Analysis (SMAA), for analyzing the stability of such parameters. The stability analysis can be used for deriving robust conclusions. SMAATRI allows ELECTRE TRI to be used with imprecise, arbitrarily distributed values for weights and the lambda cutting level. The method consists of analyzing through Monte Carlo simulation finite spaces …

Mathematical optimizationMonte Carlo methodMultiple criteriaStability (learning theory)SortingELECTRELambdaField (computer science)Analysis methodMathematics
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Observations Regarding Choice Behaviour in Interactive Multiple Criteria Decision-Making Environments: An Experimental Investigation

1989

Many interactive procedures have been developed for solving optimization problems having multiple criteria. In such procedures, an exploration over the feasible or efficient region is conducted for locating the most preferred solution. As Steuer (1986) notes, interactive procedures are characterized by phases of decision-making alternating with phases of computation. Generally a pattern is established that we keep repeating until termination. At each iteration, a solution, or group of solutions, is generated for a decision-maker’s (DM’s) examination. Based on the examination, the DM inputs information to the solution procedure in the form of tradeoffs, pairwise comparisons, aspiration level…

Mathematical optimizationOptimization problemProspect theoryGroup (mathematics)Computer scienceComputationMultiple criteriaEfficient frontierAnalytic hierarchy processPairwise comparisonSimulation
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Solving the Discrete Multiple Criteria Problem using Convex Cones

1984

An interactive method employing pairwise comparisons of attainable solutions is developed for solving the discrete, deterministic multiple criteria problem assuming a single decision maker who has an implicit quasi-concave increasing utility (or value) function. The method chooses an arbitrary set of positive multipliers to generate a proxy composite linear objective function which is then maximized over the set of solutions. The maximizing solution is compared with several solutions using pairwise judgments asked of the decision maker. Responses are used to eliminate alternatives using convex cones based on expressed preferences, and then a new set of weights is found that satisfies the i…

Mathematical optimizationStrategy and ManagementRegular polygonMultiple criteriaPairwise comparisonManagement Science and Operations ResearchDecision makerProxy (statistics)Mathematical proofMathematicsDecision analysismultiattribute programming: multiple criteria convex cones [decision analysis utility/preference]Management Science
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