Search results for "Minimax"

showing 10 items of 31 documents

Approximation properties of higher degree F-transforms based on B-splines

2015

The paper deals with the F-transform with polynomial components with respect to a generalized fuzzy partition given by B-splines. We investigate approximation properties of the inverse F-transform in this case and prove that using B-splines allows us to improve the quality of approximation of smooth functions.

Equioscillation theoremDiscrete mathematicsPolynomialApproximation theoryBox splineApproximation errorApplied mathematicsInverseSpouge's approximationMinimax approximation algorithmMathematics2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
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Groups with soluble minimax conjugate classes of subgroups

2008

A classical result of Neumann characterizes the groups in which each subgroup has finitely many conjugates only as central-by-finite groups. If $\mathfrak{X}$ is a class of groups, a group $G$ is said to have $\mathfrak{X}$-conjugate classes of subgroups if $G/core_G(N_G(H)) \in \mathfrak{X}$ for each subgroup $H$ of $G$. Here we study groups which have soluble minimax conjugate classes of subgroups, giving a description in terms of $G/Z(G)$. We also characterize $FC$-groups which have soluble minimax conjugate classes of subgroups.

Mathematics::Group TheoryT57-57.97Conjugacy classeSettore MAT/02 - AlgebraApplied mathematics. Quantitative methodsfc-groupspolycyclic groupssoluble minimax groupsSettore MAT/03 - Geometriasoluble minimax groups $FC$-groups polycyclic groups.conjugacy classes
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Applications and numerical convergence of the partial inverse method

2006

In 1983, J.E. Spingarn introduced what he called the Partial Inverse Method in the framework of Mathematical Programming. Since his initial articles, numerous applications have been given in various fields including Lagrangian multipliers methods, location theory, convex feasibility problems, analysis of data, economic equilibrium problems. In a first part of this paper we give a survey of these applications. Then by means of optimization problems relevant to location theory such as single and multifacility minimisum or minimax location problems, we examine the main advantages of the algorithm and we point out its drawbacks mainly concerning the rate of convergence. We study how different p…

Reduction (complexity)symbols.namesakeMathematical optimizationOptimization problemRate of convergenceComputer scienceLagrange multiplierConvergence (routing)symbolsOrder of accuracyMinimaxNumerical stability
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ChemInform Abstract: LOCATION OF TRANSITION STATES AND STABLE INTERMEDIATES BY MINIMAX/MINIMI OPTIMIZATION OF SYNCHRONOUS TRANSIT PATHWAYS

1983

The MINIMAX/MINIMI concept for the location of transition states and/or stable intermediates of chemical reactions is introduced, based on the synchronous transit method. According to this strategy, minimization of quadratic synchronous transit path maxima or minima is achieved by constrained exhaustive optimization of internal coordinates. The method and its efficiency are demonstrated for two-dimensional model surfaces as well as for thermally allowed electrocyclic interconversions of cyclopropyl-/allyl-cation and cyclobutene-/butadiene (gauche) within the framework of MNDO-SCF calculations. Thus, in both cases a direct comparison with the exact solution determined by minimization of the …

Maxima and minimaWork (thermodynamics)Quadratic equationChemistryNorm (mathematics)Path (graph theory)Applied mathematicsGeneral MedicineMinimaxMaximaTransition stateChemischer Informationsdienst
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The price of multiobjective robustness : Analyzing solution sets to uncertain multiobjective problems

2021

Defining and finding robust efficient solutions to uncertain multiobjective optimization problems has been an issue of growing interest recently. Different concepts have been published defining what a “robust efficient” solution is. Each of these concepts leads to a different set of solutions, but it is difficult to visualize and understand the differences between these sets. In this paper we develop an approach for comparing such sets of robust efficient solutions, namely we analyze their outcomes under the nominal scenario and in the worst case using the upper set-less order from set-valued optimization. Analyzing the set of nominal efficient solutions, the set of minmax robust efficient …

Mathematical optimizationInformation Systems and ManagementGeneral Computer ScienceComputer sciencemultiobjective robust optimizationSolution setpäätöksentukijärjestelmätManagement Science and Operations ResearchMinimaxmonitavoiteoptimointiepävarmuusIndustrial and Manufacturing Engineeringdecision makingRobustness (computer science)Modeling and Simulationuncertaintyprice of robustness
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Noncooperative dynamic games for inventory applications: A consensus approach

2008

We focus on a finite horizon noncooperative dynamic game where the stage cost of a single player associated to a decision is a monotonically nonincreasing function of the total number of players making the same decision. For the single-stage version of the game, we characterize Nash equilibria and derive a consensus protocol that makes the players converge to the unique Pareto optimal Nash equilibrium. Such an equilibrium guarantees the interests of the players and is also social optimal in the set of Nash equilibria. For the multi-stage version of the game, we present an algorithm that converges to Nash equilibria, unfortunately not necessarily Pareto optimal. The algorithm returns a seque…

TheoryofComputation_MISCELLANEOUSDynamic gamesComputer Science::Computer Science and Game TheoryMathematical optimizationCorrelated equilibriumSequential gameConsensus ProtocolsComputer scienceA-priori; Consensus protocols; Dynamic games; Finite horizons; Inventory; Inventory systems; Joint decisions; Multi stages; Nash equilibrium; Pareto-optimal; Single stages; Unilateral improvementsSymmetric equilibriumOutcome (game theory)Joint decisionsNash equilibriumFinite horizonsMulti stagessymbols.namesakeBayesian gameSettore ING-INF/04 - AutomaticaPareto-optimalA-prioriCoordination gameFolk theoremPrice of stabilityRisk dominanceNon-credible threatConsensus Protocols Dynamic Programming Game Theory InventoryInventory systemsTraveler's dilemmaNormal-form gameStochastic gameInventoryComputingMilieux_PERSONALCOMPUTINGTheoryofComputation_GENERALMinimaxConsensus protocolsEquilibrium selectionNash equilibriumBest responseSingle stagesRepeated gamesymbolsEpsilon-equilibriumSettore MAT/09 - Ricerca OperativaSolution conceptDynamic Programming Game TheoryUnilateral improvementsMathematical economicsGame theoryConsensus Protocols; Dynamic Programming Game Theory; Inventory
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On the adjoint group of some radical rings

1997

A ring R is called radical if it coincides with its Jacobson radical, which means that Rforms a group under the operation a ° b = a + b + ab for all a and b in R. This group is called the adjoint group R° of R. The relation between the adjoint group R° and the additive group R+ of a radical rin R is an interesting topic to study. It has been shown in [1] that the finiteness conditions “minimax”, “finite Prufer rank”, “finite abelian subgroup rank” and “finite torsionfree rank” carry over from the adjoint group to the additive group of a radical ring. The converse is true for the minimax condition, while it fails for all the other above finiteness conditions by an example due to Sysak [6] (s…

Pure mathematicsRing (mathematics)Group (mathematics)General MathematicsPrüfer rankRank (graph theory)Jacobson radicalAbelian groupMinimaxMathematicsAdditive groupGlasgow Mathematical Journal
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Convex semi-infinite games

1986

This paper introduces a generalization of semi-infinite games. The pure strategies for player I involve choosing one function from an infinite family of convex functions, while the set of mixed strategies for player II is a closed convex setC inRn. The minimax theorem applies under a condition which limits the directions of recession ofC. Player II always has optimal strategies. These are shown to exist for player I also if a certain infinite system verifies the property of Farkas-Minkowski. The paper also studies certain conditions that guarantee the finiteness of the value of the game and the existence of optimal pure strategies for player I.

TheoryofComputation_MISCELLANEOUSComputer Science::Computer Science and Game TheoryControl and OptimizationSemi-infiniteGeneralizationApplied MathematicsMinimax theoremComputingMilieux_PERSONALCOMPUTINGRegular polygonFunction (mathematics)Management Science and Operations ResearchBayesian gameConvex functionGame theoryMathematical economicsMathematicsJournal of Optimization Theory and Applications
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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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Minimax estimation with additional linear restrictions - a simulation study

1988

Let the parameter vector of the ordinary regression model be constrained by linear equations and in addition known to lie in a given ellipsoid. Provided the weight matrix A of the risk function has rank one, a restricted minimax estimator exists which combines both types of prior information. For general n.n.d. A two estimators as alternatives to the unfeasible exact minimax estimator are developed by minimizing an upper and a lower bound of the maximal risk instead. The simulation study compares the proposed estimators with competing least-squares estimators where remaining unknown parameters are replaced by suitable estimates.

Statistics and ProbabilityMathematical optimizationRank (linear algebra)Modeling and SimulationLinear regressionStatisticsEstimatorMinimax estimatorMinimaxEllipsoidUpper and lower boundsLinear equationMathematicsCommunications in Statistics - Simulation and Computation
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