Search results for " Robustness"

showing 10 items of 25 documents

Stationary and Initial-Terminal Value Problem for Collective Decision Making via Mean-Field Games

2017

Given a large number of homogeneous players that are distributed across three possible states, we consider the problem in which these players have to control their transition rates, following some optimality criteria. The optimal transition rates are based on the players' knowledge of their current state and of the distribution of all the other players, thus introducing mean-field terms in the running and the terminal cost. The first contribution is a mean-field model that takes into account the macroscopic and the microscopic dynamics. The second contribution is the study of the mean-field equilibrium resulting from solving the initial-terminal value problem, involving the Kolmogorov equat…

Lyapunov function0209 industrial biotechnologyMathematical optimization010102 general mathematicsMarkov processContext (language use)02 engineering and technology01 natural sciencesTerminal valueNonlinear systemsymbols.namesake020901 industrial engineering & automationStability theoryKolmogorov equationssymbolsGames Mathematical model Markov processes Sociology Statistics Microscopy RobustnessApplied mathematicsLimit (mathematics)0101 mathematicsSettore MAT/09 - Ricerca OperativaMathematics
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The facility layout problem approached using a fuzzy model and a genetic search

2005

The problem of facility layout design is discussed, taking into account the uncertainty of production scenarios and the finite production capacity of the departments. The uncertain production demand is modelled by a fuzzy number, and constrained arithmetic operators are used in order to calculate the fuzzy material handling costs. By using a ranking criterion, the layout that represents the minimum fuzzy cost is selected. A flexible bay structure is adopted as a physical model of the system while an effective genetic algorithm is implemented to search for a near optimal solution in a fuzzy contest. Constraints on the aspect ratio of the departments are taken into account using a penalty fun…

Mathematical optimizationAdaptive neuro fuzzy inference systemFitness functionFuzzy setFuzzy logicDefuzzificationIndustrial and Manufacturing EngineeringFuzzy sets genetic algorithm layout optimization robustnessFuzzy transportationArtificial IntelligenceFuzzy set operationsFuzzy numberSoftwareMathematicsJournal of Intelligent Manufacturing
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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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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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The effect of genetic robustness on evolvability in digital organisms

2008

Abstract Background Recent work has revealed that many biological systems keep functioning in the face of mutations and therefore can be considered genetically robust. However, several issues related to robustness remain poorly understood, such as its implications for evolvability (the ability to produce adaptive evolutionary innovations). Results Here, we use the Avida digital evolution platform to explore the effects of genetic robustness on evolvability. First, we obtained digital organisms with varying levels of robustness by evolving them under combinations of mutation rates and population sizes previously shown to select for different levels of robustness. Then, we assessed the abilit…

Mutation rateGenetic robustnessDigital organismsGenotypeEvolutionUNESCO::CIENCIAS DE LA VIDA::Otras especialidades de la biologíaPopulationAdaptation BiologicalEvolutionary innovationsBiologyEvolution MolecularQH359-425Computer SimulationSelection GeneticeducationEcology Evolution Behavior and Systematicseducation.field_of_studyGenetic diversityAnalysis of VarianceModels GeneticRobustness (evolution)EvolvabilityGenetic robustness; Digital organisms; Evolutionary innovationsGenetics PopulationPhenotypeEvolutionary biologyMutationTraitRna foldingAvida:CIENCIAS DE LA VIDA::Otras especialidades de la biología [UNESCO]Research ArticleBMC Evolutionary Biology
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A mesh less approch based upon Radial basis function Hermite collocation method for predicting the cooling and the freezing times of foods

2005

This work presents a meshless numerical scheme for the solution of time dependent non linear heat transfer problems in terms of a radial basis function Hermite collocation approach. The proposed scheme is applied to foodstuff's samples during freezing process; evaluation of the time evolution of the temperature profile along the sample, as well as at the core, is carried out. The moving phase-change zone is identified in the domain and plotted at several timesteps. The robustness of the proposed scheme is tested by a comparison of the obtained numerical results with those found using a Finite Volume Method and with experimental results.

Settore ING-IND/10 - Fisica Tecnica IndustrialeFoodstuff Hermite collocation Numerical scheme Time evolutionCooling Finite volume method Food processing Freezing Heat transfer Numerical analysis Robustness (control systems)Radial basis function networks
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BioAnalysis: A Framework for Structural and Functional Robustness Analysis of Metabolic Networks

2010

The main objective of this work is to analyze metabolic networks evolution in terms of their robustness and fault tolerance capabilities. In metabolic networks, errors can be seen as random removal of network nodes, while attacks are high-connectivity-degree node deletion aimed at compromising network activity. This paper proposes a software framework, namely BioAnalysis, used to test the robustness and the fault tolerance capabilities of real metabolic networks, when mutations and node deletions affect the network structure. The performed simulations are related to the central metabolic network of the well-known E. coli single-celled bacterium and involve either hub nodes or non-hub nodes,…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniBioanalysisbusiness.industryComputer scienceDistributed computingNode (networking)Metabolic networkFault tolerancecomputer.software_genreMetabolic networks hub and non-hub nodes network robustness E. coli properties analysisNetwork operations centerSoftware frameworkSoftwareRobustness (computer science)businesscomputer2010 International Conference on Complex, Intelligent and Software Intensive Systems
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METABOLIC NETWORKS ROBUSTNESS: THEORY, SIMULATIONS AND RESULTS

2011

Metabolic networks are composed of several functional modules, reproducing metabolic pathways and describing the entire cellular metabolism of an organism. In the last decade, an enormous interest has grown for the study of tolerance to errors and attacks in metabolic networks. Studies on their robustness have suggested that metabolic networks are tolerant to errors, but very vulnerable to targeted attacks against highly connected nodes. However, many findings on metabolic networks suggest that the above classification is too simple and imprecise, since hub node attacks can be by-passed if alternative metabolic paths can be exploited. On the contrary, non-hub nodes attacks can affect cell …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniCellular metabolismTheoretical computer scienceComputer Networks and Communicationsnetwork robustness and fault tolerance propertietopological analysiRobustness (evolution)Metabolic networkComputational biologyfunctional analysisComputingMethodologies_PATTERNRECOGNITIONstatistical analysiStatistical analysisOrganismMathematics
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An overview of robust Bayesian analysis

1994

Robust Bayesian analysis is the study of the sensitivity of Bayesian answers to uncertain inputs. This paper seeks to provide an overview of the subject, one that is accessible to statisticians outside the field. Recent developments in the area are also reviewed, though with very uneven emphasis. © 1994 SEIO.

Statistics and ProbabilityComputer scienceBayesian probabilitycomputer.software_genreData scienceField (computer science)Bayesian robustnessN/ARobust Bayesian analysisPrior probabilityData miningSensitivity (control systems)Statistics Probability and Uncertaintycomputer
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Structural Stability

2020

The notion of structural stability was first introduced by the Russian math- ematicians Alexandr Andronov and Lev Pontryagin (cf. Andronov and Potryangin 1937). However, there are traces of such a concept in the work of the French math- ematician Henry Poincaré (cf. Poincaré 1880). In more recent years, interesting developments about structural stability included writings of important math- ematicians like Mauricìo Peixoto (cf. at least Peixoto 1960), Stephen Smale (cf. at least Smale 1971) and René Thom (1972, 1980) (see structural morpho- dynamics). From an intuitive point of view, structural stability refers to a particular systemic property known as robustness. Put in general terms, a s…

Structural Stability Pattern Robustness dynamical systems attractorsSettore M-FIL/05 - Filosofia E Teoria Dei Linguaggi
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