Search results for "Timo"

showing 10 items of 2111 documents

L’AGRITURISMO:INCONTRO TRA AGRICOLTURA E TURISMO IN UN’OTTICA CONTEMPORANEA

2012

PSRagriturismoSettore AGR/01 - Economia Ed Estimo RuralePAC
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Prova per testimoni del pagamento e della remissione

2010

Pagamentoprova per testimoniremissioneSettore IUS/01 - Diritto Privato
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Espaces du quotidien et dynamiques de l’altérité pendant le confinement

2022

This study is the first result of the research entitled "Mon Espace Vécu" (My Lived Space) conducted in Italy during the first lockdown of 2020 (March-June), which was imposed by the government to contain the Covid-19 pandemic. During that period, the authors collected hundreds of textual testimonies from volunteers experiencing everyday spaces during the pandemic. The reflection, conducted from the perspective of cultural geography and cultural anthropology, develops from the analysis of some of these testimonies. Specifically, this paper focuses on the forms of semantization of space and the relationship between the body, space, and dynamic identity/otherness.

PandemicResearchOtherneMon Espace VécuGéographie culturelleSpaceCultural GeographyAnthropologie culturelleCovidCultural AnthropologyEspace VécuMy Lived SpaceTémoignageIdentityEspaceTestimonieLockdownLived SpaceBodySettore M-DEA/01 - Discipline DemoetnoantropologicheCovid-19Settore M-GGR/01 - GeografiaPandémieConfinement
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Analisi economica: la Redditività Nella gestione tradizionale del vigneto pantesco

2009

Il lavoro analizza la redditività del vigneto coltivato nell'isola di Pantelleria. Lo studio ha preso in esame un gruppo di aziende viticole dove si sono determinati gli impieghi di lavoro del vigneto, i materiali di origine extraziendali, e i principali parametri economici. La ricerca mette in luce l'attuale situazione economica del comparto viticolo pantesco.

Pantelleria economia viticolturaSettore AGR/01 - Economia Ed Estimo Rurale
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ANOVA-MOP: ANOVA Decomposition for Multiobjective Optimization

2018

Real-world optimization problems may involve a number of computationally expensive functions with a large number of input variables. Metamodel-based optimization methods can reduce the computational costs of evaluating expensive functions, but this does not reduce the dimension of the search domain nor mitigate the curse of dimensionality effects. The dimension of the search domain can be reduced by functional anova decomposition involving Sobol' sensitivity indices. This approach allows one to rank decision variables according to their impact on the objective function values. On the basis of the sparsity of effects principle, typically only a small number of decision variables significantl…

Pareto optimality0209 industrial biotechnologyMathematical optimizationOptimization problempäätöksenteko0211 other engineering and technologies02 engineering and technologyMulti-objective optimizationdecision makingTheoretical Computer Science020901 industrial engineering & automationsensitivity analysisDecomposition (computer science)multiple criteria optimizationdimensionality reductionMathematicsta113021103 operations researchpareto-tehokkuusDimensionality reductionta111metamodelingmonitavoiteoptimointiMetamodelingOptimization methodsSoftwareSIAM Journal on Optimization
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Treed Gaussian Process Regression for Solving Offline Data-Driven Continuous Multiobjective Optimization Problems

2023

Abstract For offline data-driven multiobjective optimization problems (MOPs), no new data is available during the optimization process. Approximation models (or surrogates) are first built using the provided offline data and an optimizer, e.g. a multiobjective evolutionary algorithm, can then be utilized to find Pareto optimal solutions to the problem with surrogates as objective functions. In contrast to online data-driven MOPs, these surrogates cannot be updated with new data and, hence, the approximation accuracy cannot be improved by considering new data during the optimization process. Gaussian process regression (GPR) models are widely used as surrogates because of their ability to pr…

Pareto optimalityComputational Mathematicspareto-tehokkuusgaussiset prosessitmetamodellingGaussian processeskrigingsurrogateregression treeskriging-menetelmämonitavoiteoptimointi
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Potential of interactive multiobjective optimization in supporting the design of a groundwater biodenitrification process

2019

The design of water treatment plants requires simultaneous analysis of technical, economic and environmental aspects, identified by multiple conflicting objectives. We demonstrated the advantages of an interactive multiobjective optimization (MOO) method over a posteriori methods in an unexplored field, namely the design of a biological treatment plant for drinking water production, that tackles the process drawbacks, contrarily to what happens in a traditional volumetric-load-driven design procedure. Specifically, we consider a groundwater denitrification biofilter, simulated by the Activated Sludge Model modified with two-stage denitrification kinetics. Three objectives were defined (nitr…

Pareto optimalityDecision support systemdecision supportEnvironmental EngineeringProcess (engineering)Computer science0208 environmental biotechnologypäätöksentukijärjestelmät02 engineering and technologyActivated sludge model010501 environmental sciencesManagement Monitoring Policy and Law01 natural sciencesMulti-objective optimizationInteractive methodIND-NIMBUSWater treatmentSensitivity (control systems)Process engineeringWaste Management and DisposalGroundwater0105 earth and related environmental sciencesvedenpuhdistusNitratesSewagepareto optimalitypareto-tehokkuusbusiness.industrywater treatmentGeneral Medicineinteractive methodvedenkäsittelymonitavoiteoptimointi020801 environmental engineeringDecision supportRange (mathematics)Decision support; IND-NIMBUS; Interactive method; NIMBUS method; Pareto optimality; Water treatment; Algorithms; Denitrification; Nitrates; Sewage; GroundwaterDenitrificationA priori and a posterioriWater treatmentNIMBUS methodbusinessAlgorithms
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Surrogate-assisted evolutionary biobjective optimization for objectives with non-uniform latencies

2018

We consider multiobjective optimization problems where objective functions have different (or heterogeneous) evaluation times or latencies. This is of great relevance for (computationally) expensive multiobjective optimization as there is no reason to assume that all objective functions should take an equal amount of time to be evaluated (particularly when objectives are evaluated separately). To cope with such problems, we propose a variation of the Kriging-assisted reference vector guided evolutionary algorithm (K-RVEA) called heterogeneous K-RVEA (short HK-RVEA). This algorithm is a merger of two main concepts designed to account for different latencies: A single-objective evolutionary a…

Pareto optimalityMathematical optimizationComputer science0211 other engineering and technologiesEvolutionary algorithm02 engineering and technologyexpensive optimizationMulti-objective optimizationEvolutionary computationSet (abstract data type)optimointi0202 electrical engineering electronic engineering information engineeringmetamodellingRelevance (information retrieval)multiobjective optimizationBayesian optimizationta113021103 operations researchpareto-tehokkuusbayesilainen menetelmäBayesian optimizationmonitavoiteoptimointimachine learningkoneoppiminenheterogeneous objectivesBenchmark (computing)020201 artificial intelligence & image processing
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A New Hybrid Mutation Operator for Multiobjective Optimization with Differential Evolution

2011

Differential evolution has become one of the most widely used evolution- ary algorithms in multiobjective optimization. Its linear mutation operator is a sim- ple and powerful mechanism to generate trial vectors. However, the performance of the mutation operator can be improved by including a nonlinear part. In this pa- per, we propose a new hybrid mutation operator consisting of a polynomial based operator with nonlinear curve tracking capabilities and the differential evolution’s original mutation operator, to be efficiently able to handle various interdependencies between decision variables. The resulting hybrid operator is straightforward to implement and can be used within most evoluti…

Pareto optimalityMathematical optimizationEvolutionary algorithmComputational intelligenceMOEA/DNonlinearGenetic operatorEvolutionary algorithmsMulti-objective optimizationPolynomialTheoretical Computer ScienceDEOperator (computer programming)Evolutionary algorithms; DE; Nonlinear; Multi-criteria optimization; Polynomial; Pareto optimality; MOEA/DPareto-optimaalisuusMathematicsMatematikMulti-criteria optimizationState (functional analysis)monitavoiteoptimointiNonlinear systemDifferential evolutionGeometry and TopologyAlgorithmSoftwareMathematics
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PAINT : Pareto front interpolation for nonlinear multiobjective optimization

2011

A method called PAINT is introduced for computationally expensive multiobjective optimization problems. The method interpolates between a given set of Pareto optimal outcomes. The interpolation provided by the PAINT method implies a mixed integer linear surrogate problem for the original problem which can be optimized with any interactive method to make decisions concerning the original problem. When the scalarizations of the interactive method used do not introduce nonlinearity to the problem (which is true e.g., for the synchronous NIMBUS method), the scalarizations of the surrogate problem can be optimized with available mixed integer linear solvers. Thus, the use of the interactive meth…

Pareto optimalityMathematical optimizationMatematikControl and OptimizationApplied MathematicsComputationally expensive problemsMulti-objective optimizationmonitavoiteoptimointiSet (abstract data type)Computational MathematicsPareto optimalNonlinear systemMultiobjective optimization problemapproksimaatioPareto-optimaalisuusapproksimointiAlgorithmApproximationMathematicsInterpolationMathematicsInteger (computer science)Multiobjective optimizationInteractive decision making
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