Search results for "Active methods"

showing 10 items of 35 documents

DESDEO: The Modular and Open Source Framework for Interactive Multiobjective Optimization

2021

Interactive multiobjective optimization methods incorporate preferences from a human decision maker in the optimization process iteratively. This allows the decision maker to focus on a subset of solutions, learn about the underlying trade-offs among the conflicting objective functions in the problem and adjust preferences during the solution process. Incorporating preference information allows computing only solutions that are interesting to the decision maker, decreasing computation time significantly. Thus, interactive methods have many strengths making them viable for various applications. However, there is a lack of existing software frameworks to apply and experiment with interactive …

0209 industrial biotechnologylineaarinen optimointiPareto optimizationGeneral Computer Sciencemulti-criteria decision makingComputer sciencepäätöksentekoevoluutiolaskenta02 engineering and technologyData-driven multiobjective optimizationcomputer.software_genrenonlinear optimizationMulti-objective optimizationData modelingopen source softwareavoin lähdekoodi020901 industrial engineering & automationSoftwareoptimointi0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceUse casecomputer.programming_languageGraphical user interfacepareto-tehokkuusbusiness.industryGeneral Engineeringinteractive methodsModular designPython (programming language)monitavoiteoptimointiTK1-9971Software frameworkdata-driven multiobjective optimizationevolutionary computation020201 artificial intelligence & image processingElectrical engineering. Electronics. Nuclear engineeringbusinessSoftware engineeringcomputerIEEE Access
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Comparing interactive evolutionary multiobjective optimization methods with an artificial decision maker

2021

AbstractSolving multiobjective optimization problems with interactive methods enables a decision maker with domain expertise to direct the search for the most preferred trade-offs with preference information and learn about the problem. There are different interactive methods, and it is important to compare them and find the best-suited one for solving the problem in question. Comparisons with real decision makers are expensive, and artificial decision makers (ADMs) have been proposed to simulate humans in basic testing before involving real decision makers. Existing ADMs only consider one type of preference information. In this paper, we propose ADM-II, which is tailored to assess several …

021103 operations researchPerformance comparison0211 other engineering and technologiesevoluutiolaskentapäätöksentukijärjestelmät02 engineering and technologymonitavoiteoptimointiMany-objective optimizationComputational MathematicsArtificial Intelligenceinteraktiivisuus0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingEngineering (miscellaneous)Interactive methodsInformation SystemsComplex & Intelligent Systems
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A New Paradigm in Interactive Evolutionary Multiobjective Optimization

2020

Over the years, scalarization functions have been used to solve multiobjective optimization problems by converting them to one or more single objective optimization problem(s). This study proposes a novel idea of solving multiobjective optimization problems in an interactive manner by using multiple scalarization functions to map vectors in the objective space to a new, so-called preference incorporated space (PIS). In this way, the original problem is converted into a new multiobjective optimization problem with typically fewer objectives in the PIS. This mapping enables a modular incorporation of decision maker’s preferences to convert any evolutionary algorithm to an interactive one, whe…

050101 languages & linguisticsMathematical optimizationComputer sciencemedia_common.quotation_subjectdecision makerEvolutionary algorithmpäätöksentukijärjestelmätevoluutiolaskentapreference information02 engineering and technologySpace (commercial competition)Multi-objective optimizationoptimointiachievement scalarizing functionsalgoritmit0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesQuality (business)evolutionary algorithmsFunction (engineering)media_commonbusiness.industry05 social sciencesinteractive methodsModular designDecision makermonitavoiteoptimointiPreference020201 artificial intelligence & image processingbusiness
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LR-NIMBUS : an interactive algorithm for uncertain multiobjective optimization with lightly robust efficient solutions

2022

In this paper, we develop an interactive algorithm to support a decision maker to find a most preferred lightly robust efficient solution when solving uncertain multiobjective optimization problems. It extends the interactive NIMBUS method. The main idea underlying the designed algorithm, called LR-NIMBUS, is to ask the decision maker for a most acceptable (typical) scenario, find an efficient solution for this scenario satisfying the decision maker, and then apply the derived efficient solution to generate a lightly robust efficient solution. The preferences of the decision maker are incorporated through classifying the objective functions. A lightly robust efficient solution is generated …

Control and OptimizationApplied Mathematicspäätöksentekolight robust efficiencyrobust optimizationmatemaattiset menetelmätportfoliotManagement Science and Operations Researchinteractive methodsarvopaperisalkutskenaariotepävarmuusmonitavoiteoptimointiComputer Science Applicationsuncertain multiple criteria optimizationmenetelmätoptimointialgoritmitinteraktiivisuusBusiness Management and Accounting (miscellaneous)portfolio selection
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Optimistic NAUTILUS navigator for multiobjective optimization with costly function evaluations

2022

AbstractWe introduce novel concepts to solve multiobjective optimization problems involving (computationally) expensive function evaluations and propose a new interactive method called O-NAUTILUS. It combines ideas of trade-off free search and navigation (where a decision maker sees changes in objective function values in real time) and extends the NAUTILUS Navigator method to surrogate-assisted optimization. Importantly, it utilizes uncertainty quantification from surrogate models like Kriging or properties like Lipschitz continuity to approximate a so-called optimistic Pareto optimal set. This enables the decision maker to search in unexplored parts of the Pareto optimal set and requires …

Control and Optimizationdecision makersApplied Mathematicspäätöksentekopreference informationManagement Science and Operations Researchinteractive methodsmonitavoiteoptimointiComputer Science ApplicationsoptimointiBusiness Management and Accounting (miscellaneous)multiobjective optimization problemskrigingmallit (mallintaminen)kriging-menetelmäcomputational cost
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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
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Solving multiobjective optimization problems with decision uncertainty: an interactive approach

2018

We propose an interactive approach to support a decision maker to find a most preferred robust solution to multiobjective optimization problems with decision uncertainty. A new robustness measure that is understandable for the decision maker is incorporated as an additional objective in the problem formulation. The proposed interactive approach utilizes elements of the synchronous NIMBUS method and is aimed at supporting the decision maker to consider the objective function values and the robustness of a solution simultaneously. In the interactive approach, we offer different alternatives for the decision maker to express her/his preferences related to the robustness of a solution. To conso…

Economics and EconometricsMathematical optimization050208 financerobust solutionsComputer science05 social sciencesmultiple criteria decision makinginteractive methodsDecision makerNIMBUSmonitavoiteoptimointiVisualizationMultiobjective optimization problemRobustness (computer science)0502 economics and businesshandling uncertaintiesrobustness measureBusiness and International Management050203 business & managementJournal of Business Economics
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Interaktīvo metožu efektiviāte, mācot angļu valodas gramatiku vidusskolā

2016

Bakalaura darba mērķis ir pierādīt interaktīvo metožu efektivitāti, mācot saliktās tagadnes laiku angļu valodā. Šis pētījums sastāv četrām nodaļām. Pirmajā nodaļā akcentēts angļu valodas gramatikas nozīmīgums un sniegts ieskats gramatikas teorijā. Tiek aprakstītas galvenās iezīmes un atšķirības mutvārdu un rakstveida gramatikā, kā arī minēts, kāpēc angļu valodas gramatika būtu jāmāca un aprakstīta skolotāja loma mācību procesā. Otrajā nodaļā pētītas dažādas angļu valodas gramatikas mācīšanas tehnikas un metodes. Trešajā nodaļā aprakstīti interaktīvie paņēmieni, mācot angļu valodas gramatiku vidusskolā. Bakalaura darba praktiskā daļa ietver eksperimentu. Šī daļa veltīta novadīto stundu aprak…

English grammarValodniecībateaching methodsinteractive methodsquasi – experimentcommunicative approach
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An Interactive Simple Indicator-Based Evolutionary Algorithm (I-SIBEA) for Multiobjective Optimization Problems

2015

This paper presents a new preference based interactive evolutionary algorithm (I-SIBEA) for solving multiobjective optimization problems using weighted hypervolume. Here the decision maker iteratively provides her/his preference information in the form of identifying preferred and/or non-preferred solutions from a set of nondominated solutions. This preference information provided by the decision maker is used to assign weights of the weighted hypervolume calculation to solutions in subsequent generations. In any generation, the weighted hypervolume is calculated and solutions are selected to the next generation based on their contribution to the weighted hypervolume. The algorithm is compa…

Flexibility (engineering)Set (abstract data type)Mathematical optimizationComputer scienceBenchmark (computing)Evolutionary algorithmmultiobjective optimizationInteractive evolutionary computationevolutionary algorithmsinteractive methodsMulti-objective optimizationEvolutionary programmingPreference
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Assessing the Performance of Interactive Multiobjective Optimization Methods

2021

Interactive methods are useful decision-making tools for multiobjective optimization problems, because they allow a decision-maker to provide her/his preference information iteratively in a comfortable way at the same time as (s)he learns about all different aspects of the problem. A wide variety of interactive methods is nowadays available, and they differ from each other in both technical aspects and type of preference information employed. Therefore, assessing the performance of interactive methods can help users to choose the most appropriate one for a given problem. This is a challenging task, which has been tackled from different perspectives in the published literature. We present a …

General Computer ScienceComputer sciencepäätöksenteko0211 other engineering and technologiespreference information02 engineering and technologyMachine learningcomputer.software_genreMulti-objective optimizationTheoretical Computer ScienceTask (project management)menetelmätoptimointi0202 electrical engineering electronic engineering information engineering021103 operations researchbusiness.industryinteractive methodsmonitavoiteoptimointidecision-makersPreferenceVariety (cybernetics)Multiobjective optimization probleminteraktiivisuusmultiobjective optimization problems020201 artificial intelligence & image processingperformance assessmentArtificial intelligencebusinesscomputerACM Computing Surveys
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