Search results for " set"

showing 10 items of 2095 documents

Metric regularity and second-order necessary optimality conditions for minimization problems under inclusion constraints

1994

In this paper, we establish some general metric regularity results for multivalued functions on Banach spaces. Then, we apply them to derive second-order necessary optimality conditions for the problem of minimizing a functionf on the solution set of an inclusion 0?F(x) withx?C, whenF has a closed convex second-order derivative.

Mathematical optimizationControl and OptimizationMultivalued functionApplied MathematicsTheory of computationSolution setRegular polygonBanach spaceMinificationManagement Science and Operations ResearchDirectional derivativeMathematicsJournal of Optimization Theory and Applications
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Team Theory and Person-by-Person Optimization with Binary Decisions

2012

In this paper, we extend the notion of person-by-person (pbp) optimization to binary decision spaces. The novelty of our approach is the adaptation to a dynamic team context of notions borrowed from the pseudo-boolean optimization field as completely local-global or unimodal functions and submodularity. We also generalize the concept of pbp optimization to the case where groups of $m$ decisions makers make joint decisions sequentially, which we refer to as $m$b$m$ optimization. The main contribution is a description of sufficient conditions, verifiable in polynomial time, under which a pbp or an $m$b$m$ optimization algorithm converges to the team-optimum. As a second contribution, we prese…

Mathematical optimizationControl and Optimizationcontrol optimizationBinary decision diagramApplied MathematicsTeam Theory; Person-by-Person Optimization; Pseudo-Boolean OptimizationApproximation algorithmState vectorTeam TheoryPerson-by-Person OptimizationSubmodular set functionVector optimizationPseudo-Boolean OptimizationComplete informationSettore MAT/09 - Ricerca OperativaGreedy algorithmTime complexityMathematicsSIAM Journal on Control and Optimization
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A Stochastic Search on the Line-Based Solution to Discretized Estimation

2012

Published version of a chapter in the book: Advanced Research in Applied Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-31087-4_77 Recently, Oommen and Rueda [11] presented a strategy by which the parameters of a binomial/multinomial distribution can be estimated when the underlying distribution is nonstationary. The method has been referred to as the Stochastic Learning Weak Estimator (SLWE), and is based on the principles of continuous stochastic Learning Automata (LA). In this paper, we consider a new family of stochastic discretized weak estimators pertinent to tracking time-varying binomial distributions. As opposed to the SLWE, our p…

Mathematical optimizationDiscretizationLearning automataComputer scienceStochastic Point Locationlearning automataEstimatorVDP::Technology: 500::Information and communication technology: 550020206 networking & telecommunications02 engineering and technologyOracleVDP::Mathematics and natural science: 400::Information and communication science: 420::Knowledge based systems: 425weak estimatorsnon-stationary environmentsLine (geometry)Convergence (routing)0202 electrical engineering electronic engineering information engineeringApplied mathematics020201 artificial intelligence & image processingMultinomial distributionFinite set
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Voltage Regulation and Power Losses Minimization in Automated Distribution Networks by an Evolutionary Multiobjective Approach

2004

In this paper, the problem of voltage regulation and power losses minimization for automated distribution systems is dealt with. The classical formulation of the problem of optimal control of shunt capacitor banks and Under Load Tap Changers located at HV/MV substations has been coupled with the optimal control of tie-switches and capacitor banks on the feeders of a large radially operated meshed distribution system with the aim of attaining minimum power losses and the flattening of the voltage profile. The considered formulation requires the optimization of two different objectives; therefore the use of adequate multiobjective heuristic optimization methods is needed. The heuristic strate…

Mathematical optimizationEngineeringbusiness.industryFuzzy setEnergy Engineering and Power TechnologyOptimal controlEvolutionary computationFlatteninglaw.inventionSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaCapacitorOptimal control optimization methods power distribution voltage control.Control theorylawMinificationVoltage regulationElectrical and Electronic EngineeringbusinessVoltage
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On central algorithms of approximation under fuzzy information

2005

We consider the problem of approximation of an operator by information described by n real characteristics in the case when this information is fuzzy. We develop the well-known idea of an optimal error method of approximation for this case. It is a method whose error is the infimum of the errors of all methods for a given problem characterized by fuzzy numbers in this case. We generalize the concept of central algorithms, which are always optimal error algorithms and in the crisp case are useful both in practice and in theory. In order to do this we define the centre of an L-fuzzy subset of a normed space. The introduced concepts allow us to describe optimal methods of approximation for lin…

Mathematical optimizationFuzzy classificationArtificial IntelligenceLogicApproximation errorFuzzy setFuzzy set operationsFuzzy numberApproximation algorithmRound-off errorAlgorithmFuzzy logicMathematicsFuzzy Sets and Systems
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Fuzzy expected utility

1984

Decision making under uncertainty requires not only measures of the uncertainty of situations that we try to recognize , but also an estimate of the imprecision from which they are determined. This imprecision can be the result either of a lack of exactness in the measure of the elements which are necessary to the determination of the states of nature or the purely subjective interpretation of these states. Through a subjective measure of the non-measurable imprecision, the purpose of the fuzzy expected utility, which is investigated, is to translate with a great accuracy the imprecise behaviour of the decision-maker in an uncertain world. Consequently we propose to introduce first the prob…

Mathematical optimizationFuzzy classificationFuzzy measure theoryLogicbusiness.industry[SHS.ECO]Humanities and Social Sciences/Economics and FinanceType-2 fuzzy sets and systemsFuzzy logicDefuzzificationArtificial IntelligenceFuzzy mathematicsFuzzy numberFuzzy set operations[ SHS.ECO ] Humanities and Social Sciences/Economies and financesArtificial intelligencebusiness[SHS.ECO] Humanities and Social Sciences/Economics and FinanceDecision makingFuzzyMathematics
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The fuzzy p-median problem

2004

In many location models, the strong crisp assumptions, like known demands and distances, are not realistic in most cases. The fuzzy p-median problem relaxes this hypothesis giving to the decision maker a necessary degree of freedom to solve real-world problems. It allows a decision maker to improve an optimal covering of a location problem by considering partially feasible solutions in which some demand is left uncovered. Here we revise the main facts and results about this problem emphasising different specific algorithms of resolution. Finally we show that this fuzzy version can be used to analyse the global structure of a given instance of the crisp problem.

Mathematical optimizationFuzzy classificationFuzzy transportationComputer scienceFuzzy setGeneral EngineeringFuzzy set operationsFuzzy numberType-2 fuzzy sets and systemsGeneral Business Management and AccountingDefuzzificationFuzzy logicInternational Journal of Technology, Policy and Management
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Soft-computing based heuristics for location on networks: The p-median problem

2011

We propose a genetic algorithm for the fuzzy p-median problem in which the optimal transport cost of the associated crisp problem is unknown. Our algorithm works with two populations: in one, the solutions with a better crisp transport cost are favored by the selection criterion, whereas in the second one, solutions with a better fuzzy satisfaction level are preferred. These populations are not independent. On the contrary, the first one periodically invades the second one, thus providing new starting points for finding fuzzy improvements. Our computational results also reveal the importance of choosing adequate functions for selecting the parents. Our best results are obtained with functio…

Mathematical optimizationFuzzy classificationFuzzy transportationFuzzy setFuzzy numberFuzzy set operationsFuzzy logicDefuzzificationSoftwareMembership functionMathematicsApplied Soft Computing
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Involving fuzzy orders for multi-objective linear programming

2012

This paper presents a solution approach for multi-objective linear programming problem. We propose to involve fuzzy order relations to describe the objective functions where in ”classical” fuzzy approach the membership functions which illustrate how far the concrete point is from the solution of individual problem are studied. Further the global fuzzy order relation is constructed by aggregating the individual fuzzy order relations. Thus the global fuzzy relation contains the information about all objective functions and in the last step we find a maximum in the set of constrains with respect to the global fuzzy order relation. We illustrate this approach by an example.

Mathematical optimizationFuzzy classificationMathematics::General MathematicsFuzzy setmulti-objective linear programmingfuzzy order relationType-2 fuzzy sets and systemsDefuzzificationModeling and SimulationFuzzy mathematicsQA1-939aggregation of fuzzy relationsFuzzy numberFuzzy set operationsMathematicsAnalysisMembership functionMathematicsMathematical Modelling and Analysis
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Controller Design Under Fuzzy Pole-Placement Specifications: An Interval Arithmetic Approach

2006

This paper discusses fuzzy specifications for robust controller design, as a way to define different specification levels for different plants in a family and allow the control of performance degradation. Controller synthesis will be understood as mapping a fuzzy plant onto a desired fuzzy set of closed-loop specifications. In this context, a fuzzy plant is considered as a possibility distribution on a given plant space. In particular, pole placement in linear plants with fuzzy parametric uncertainty is discussed, although the basic idea is general and could be applied to other settings. In the case under consideration, the controller coefficients are the solution of a fuzzy linear system o…

Mathematical optimizationFuzzy classificationNeuro-fuzzyApplied MathematicsFuzzy control systemType-2 fuzzy sets and systemsDefuzzificationFuzzy logicComputational Theory and MathematicsArtificial IntelligenceControl and Systems EngineeringControl theoryFuzzy set operationsFuzzy numberComputingMethodologies_GENERALMathematicsIEEE Transactions on Fuzzy Systems
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