Search results for "Decision maker"

showing 10 items of 48 documents

Interactive Method NIMBUS for Nondifferentiable Multiobjective Optimization Problems

1997

An interactive method, NIMBUS, for nondifferentiable multiobjective optimization problems is introduced. The method is capable of handling several nonconvex locally Lipschitzian objective functions subject to nonlinear (possibly nondifferentiable) constraints. The idea of NIMBUS is that the decision maker can easily indicate what kind of improvements are desired and what kind of impairments are tolerable at the point considered. The decision maker is asked to classify the objective functions into five different classes: those to be improved, those to be improved down to some aspiration level, those to be accepted as they are, those to be impaired till some upper bound, and those allowed to …

Mathematical optimizationNonlinear systemMultiobjective optimization problemComputer sciencePoint (geometry)Aspiration levelDecision makerUpper and lower boundsMulti-objective optimization
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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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Decision making in multiobjective optimization problems under uncertainty: balancing between robustness and quality

2018

As an emerging research field, multiobjective robust optimization employs minmax robustness as the most commonly used concept. Light robustness is a concept in which a parameter, tolerable degradations, can be used to control the loss in the objective function values in the most typical scenario for gaining in robustness. In this paper, we develop a lightly robust interactive multiobjective optimization method, LiRoMo, to support a decision maker to find a most preferred lightly robust efficient solution with a good balance between robustness and the objective function values in the most typical scenario. In LiRoMo, we formulate a lightly robust subproblem utilizing an achievement scalarizi…

Mathematical optimizationdecision supportOptimization problemmultiobjective robust optimizationComputer sciencepäätöksenteko0211 other engineering and technologies02 engineering and technologyManagement Science and Operations ResearchMulti-objective optimizationoptimointiRobustness (computer science)0502 economics and business050210 logistics & transportation021103 operations research05 social scienceslight robust efficiencyRobust optimizationinteractive methodshandling uncertaintyDecision makerMinimaxmonitavoiteoptimointiepävarmuusVisualizationMultiobjective optimization problemtrade-off between robustness and qualityBusiness Management and Accounting (miscellaneous)OR Spectrum
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NIMBUS — Interactive Method for Nondifferentiable Multiobjective Optimization Problems

1996

An interactive method, NIMBUS, for nondifferentiable multiobjective optimization problems is introduced. We assume that every objective function is to be minimized The idea of NIMBUS is that the decision maker can easily indicate what kind of improvements are desired and what kind of impairments are tolerable at the point considered.

Multiobjective optimization problemMathematical optimizationPoint (geometry)Decision makerBundle methodsMulti-objective optimizationMathematics
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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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An Effort-Accuracy Framework for IIMT

2011

In this chapter, we analyze to what extent INTACMATO meets the requirement of low effort. We take an existing effort-accuracy model, adapt and extend it to INTACMATO and show analytically the savings of effort achieved.

Operations researchComputer scienceDecision strategyDecision makerAttribute level
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NAUTILUS framework : towards trade-off-free interaction in multiobjective optimization

2016

In this paper, we present a framework of different interactive NAUTILUS methods for multiobjective optimization. In interactive methods, the decision maker iteratively sees solution alternatives and provides one’s preferences in order to find the most preferred solution. We question the widely used setting that the solutions shown to the decision maker should all be Pareto optimal which implies that improvement in any objective function necessitates allowing impairment in some others. Instead, in NAUTILUS we enable the decision maker to make a free search without having to trade-off by starting from an inferior solution and iteratively approaching the Pareto optimal set by allowing all obje…

Pareto optimalityEconomics and EconometricsEngineeringMathematical optimization021103 operations researchbiologybusiness.industry0211 other engineering and technologies02 engineering and technologyinteractive methodsDecision makerbiology.organism_classificationMulti-objective optimizationSet (abstract data type)Pareto optimalOrder (exchange)0202 electrical engineering electronic engineering information engineeringmulticriteria optimization020201 artificial intelligence & image processingPreference elicitationBusiness and International ManagementNautilusbusiness
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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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Approximation method for computationally expensive nonconvex multiobjective optimization problems

2012

Pareto-tehokkuusPareto optimalitycomputational efficiencyPareto front approximationpäätöksentekodecision makerpsychological convergencemonitavoiteoptimointilaskennallinen vaativuussurrogate functioninteractive decision makingmenetelmätPareto-optimointioptimointilaskennalliset menetelmätmultiobjective optimizationPareto dominancyapproksimointicomputational cost
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Measurement of B- mixing at the Z

1991

Abstract From more than 175 000 hadronic Z decays observed with the ALEPH detector at LEP, we select 823 events with pairs of leptons in the final state. From these we measure χ , the probability thata b hadron which is observed to decay originated as a b hadron. We find χ =0.132 −0.026 +0.027 .

PhysicsNuclear and High Energy PhysicsParticle physicsAlephElectron–positron annihilationHigh Energy Physics::PhenomenologyHadronDecision makerMeasure (mathematics)Nuclear physicsHigh Energy Physics::ExperimentNuclear ExperimentMixing (physics)LeptonPhysics Letters B
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