Search results for "multicriteria optimization"

showing 5 items of 5 documents

Survey of methods to visualize alternatives in multiple criteria decision making problems

2012

When solving decision problems where multiple conflicting criteria are to be considered simultaneously, decision makers must compare several different alternatives and select the most preferred one. The task of comparing multidimensional vectors is very demanding for the decision maker without any support. Different graphical visualization tools can be used to support and help the decision maker in understanding similarities and differences between the alternatives and graphical illustration is a very important part of decision support systems that are used in solving multiple criteria decision making problems. The visualization task is by no means trivial because, on the one hand, the grap…

Decision support systemComputer sciencevisualisointiDecision treeManagement Science and Operations Researchgraafinen kuvituscomparison of alternativesmulticriteria optimizationInfluence diagramirralliset vaihtoehdotmultiobjective optimizationvaihtoehtojen vertailudiscrete alternativesvisualizationMCDMDecision engineeringpareto optimalityManagement scienceEvidential reasoning approachinteractive methodsMultiple-criteria decision analysisgraphical illustrationBusiness Management and Accounting (miscellaneous)päätösanalyysiDecision analysisOptimal decisionOR Spectrum
researchProduct

A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms

2017

Evolutionary algorithms are widely used for solving multiobjective optimization problems but are often criticized because of a large number of function evaluations needed. Approximations, especially function approximations, also referred to as surrogates or metamodels are commonly used in the literature to reduce the computation time. This paper presents a survey of 45 different recent algorithms proposed in the literature between 2008 and 2016 to handle computationally expensive multiobjective optimization problems. Several algorithms are discussed based on what kind of an approximation such as problem, function or fitness approximation they use. Most emphasis is given to function approxim…

0209 industrial biotechnologyMathematical optimizationComputer scienceComputationEvolutionary algorithmComputational intelligence02 engineering and technologyMulti-objective optimizationTheoretical Computer Science020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineeringmulticriteria optimizationsurrogateresponse surface approximationcomputational costmetamodelFitness approximationpareto optimalitypareto-tehokkuusFunction (mathematics)monitavoiteoptimointiFunction approximationkoneoppiminen020201 artificial intelligence & image processingGeometry and TopologySoftware
researchProduct

Comparing reference point based interactive multiobjective optimization methods without a human decision maker

2022

AbstractInteractive multiobjective optimization methods have proven promising in solving optimization problems with conflicting objectives since they iteratively incorporate preference information of a decision maker in the search for the most preferred solution. To find the appropriate interactive method for various needs involves analysis of the strengths and weaknesses. However, extensive analysis with human decision makers may be too costly and for that reason, we propose an artificial decision maker to compare a class of popular interactive multiobjective optimization methods, i.e., reference point based methods. Without involving any human decision makers, the artificial decision make…

interactive multiobjective optimizationControl and OptimizationApplied MathematicspäätöksentekopäätöksentukijärjestelmätManagement Science and Operations ResearchmonitavoiteoptimointiComputer Science Applicationskoneoppiminenmulticriteria optimizationlearning phaseinteraktiivisuusBusiness Management and Accounting (miscellaneous)performance comparisondecision phasereference pointJournal of Global Optimization
researchProduct

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
researchProduct

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
researchProduct