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showing 10 items of 2078 documents

Design of sheet stamping operations to control springback and thinning: a multi-objective stochastic optimization approach

2010

Abstract The aim of this paper is to develop a design tool for stamping processes, which is able to deal with the scattering of the final part quality due to the inner variability of such operations. Such variability is one of the main drawbacks for a robust process design. It results in a scattering of the most significant process results and depends on several parameters. The so called noise factors greatly influence final result variability, which often means rejecting parts and anyway achieving final properties different from the specified ones. The process investigated in the paper is an S-shaped U-channel stamping operation carried out on a lightweight aluminum alloy of automotive int…

Mathematical optimizationEngineeringFEMOptimization problemSpringbackbusiness.industryMechanical EngineeringDesign toolStochastic optimizationProcess designStampingCondensed Matter PhysicsStochastic programmingMechanics of MaterialsDesign processGeneral Materials ScienceStochastic optimizationEngineering design processbusinessThinningResponse Surface MethodologySettore ING-IND/16 - Tecnologie E Sistemi Di LavorazioneSimulationCivil and Structural Engineering
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A Comparative Analysis of Different Robust Design Approaches in Sheet Stamping Operations

2011

A crucial issue in sheet stamping optimization problems is related to the process robustness improvement: critical scattering in the investigated performances arises due to some noise variables influence, often evolving up design failure itself. In fact, strong variations in the final stamped part or fluctuations of strain distribution may lead to an uncontrolled process design. Such variability cannot be controlled but anyway it is possible to develop proper design tools able to identify robust process calibrations above which the noises variations effects are admissible. In this paper, a multi‐objective optimization problem was analyzed, with the aim to minimize both excessive thinning an…

Mathematical optimizationEngineeringFEMOptimization problembusiness.industryStochastic processProcess designStampingmeta-modelingFinite element methodReliability engineeringRobust designspringbackmulti-objective optimizationRobustness (computer science)Strain distributionrobust designbusinessThinningSettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazione
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A NEW PROGRESSIVE DESIGN METHODOLOGY FOR COMPLEX SHEET METAL STAMPING OPERATIONS: COUPLING SPATIALLY DIFFERENTIATED RESTRAINING FORCES APPROACH AND M…

2010

The growing interest in sheet metal stamping processes, particularly in the automotive industry has led to three main issues in this field:*request of very complex shapes; *growing interest in springback control; *solution of multi-objective problems. These issues make a sheet metal stamping processes design very difficult and proper design methodologies to reduce times and costs are highly required. In this paper, a computer aided approach aiming to satisfy the mentioned issues is proposed. In particular, a progressive design approach based on the integration between numerical simulations, Response Surface Methodology (RSM) and Pareto optimal solutions search techniques was applied in orde…

Mathematical optimizationEngineeringbusiness.industryMechanical EngineeringPareto principleAutomotive industrymulti-objective optimisatiomrestraining forces stategyProcess designStampingSheet metal formingMulti-objective optimizationComputer Science ApplicationsspringbackModeling and SimulationDesign processGeneral Materials SciencebusinessEngineering design processDesign methodsSettore ING-IND/16 - Tecnologie E Sistemi Di LavorazioneCivil and Structural Engineering
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Some improvements in solving radial distributions networks through the backward/forward method

2005

In the electrical radial distribution networks analysis, the backward/forward method shows good features in terms of robustness, independence from load nature, small use of hardware resources and limited calculation time. In the present paper, some procedures to improve the b/f method with the aim of reducing the calculation time are presented. The adopted procedures regard the choice of the initial values of the nodes voltages and the way in which the convergence criterion is applied. The results of some tests carried out on some electrical test systems here reported have shown the efficiency of the proposed methodology in terms of calculation time reduction, especially when solving heavil…

Mathematical optimizationEngineeringbusiness.industrySystem testingAC powerAutomationlaw.inventionSettore ING-IND/33 - Sistemi Elettrici Per L'Energiasymbols.namesakeCapacitorlawRobustness (computer science)symbolsPower-flow studybusinessBackward/forward method Load flow analysis Power DistributionNewton's methodVoltage2005 IEEE Russia Power Tech
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A tabu thresholding algorithm for arc crossing minimization in bipartite graphs

1996

Acyclic directed graphs are commonly used to model complex systems. The most important criterion to obtain a readable map of an acyclic graph is that of minimizing the number of arc crossings. In this paper, we present a heuristic for solving the problem of minimizing the number of arc crossings in a bipartite graph. It consists of a novel and easier implementation of fundamental tabu search ideas without explicit use of memory structures (a tabu thresholding approach). Computational results are reported on a set of 250 randomly generated test problems. Our algorithm has been compared with the two best heuristics published in the literature and with the optimal solutions for the test proble…

Mathematical optimizationGeneral Decision SciencesComparability graphDirected graphManagement Science and Operations ResearchDirected acyclic graphFeedback arc setTabu searchlaw.inventionlawLine graphBipartite graphMathematicsofComputing_DISCRETEMATHEMATICSMoral graphMathematicsAnnals of Operations Research
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Path relinking and GRG for artificial neural networks

2006

Artificial neural networks (ANN) have been widely used for both classification and prediction. This paper is focused on the prediction problem in which an unknown function is approximated. ANNs can be viewed as models of real systems, built by tuning parameters known as weights. In training the net, the problem is to find the weights that optimize its performance (i.e., to minimize the error over the training set). Although the most popular method for training these networks is back propagation, other optimization methods such as tabu search or scatter search have been successfully applied to solve this problem. In this paper we propose a path relinking implementation to solve the neural ne…

Mathematical optimizationInformation Systems and ManagementTraining setGeneral Computer ScienceArtificial neural networkComputer sciencebusiness.industryManagement Science and Operations ResearchSolverIndustrial and Manufacturing EngineeringBackpropagationEvolutionary computationTabu searchNonlinear programmingSearch algorithmModeling and SimulationArtificial intelligencebusinessMetaheuristicEuropean Journal of Operational Research
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Robust control of uncertain multi-inventory systems via linear matrix inequality

2008

We consider a continuous time linear multi inventory system with unknown demands bounded within ellipsoids and controls bounded within ellipsoids or polytopes. We address the problem of "-stabilizing the inventory since this implies some reduction of the inventory costs. The main results are certain conditions under which "-stabilizability is possible through a saturated linear state feedback control. All the results are based on a Linear Matrix Inequalities (LMIs) approach and on some recent techniques for the modeling and analysis of polytopic systems with saturations.

Mathematical optimizationLinear Matrix InequalitiesPolytopeDynamical Systems (math.DS)stock control93xxcontinuous systems linear matrix inequalities linear systems manufacturing systems robust control state feedback stock control uncertain systemsimpulse control inventory control hybrid systemsSettore ING-INF/04 - AutomaticaControl theoryFOS: Mathematicsmanufacturing systemsMathematics - Dynamical Systemslinear matrix inequalitiesstate feedbackTime complexityMathematics - Optimization and ControlInventory systemsMathematicsInventory controlLinear Matrix Inequalities; Inventory systemsLinear systemlinear systemsLinear matrix inequality93Cxx;93xxLinearity93Cxxhybrid systemsEllipsoidComputer Science Applicationsimpulse control; inventory control; hybrid systemsuncertain systemsControl and Systems EngineeringOptimization and Control (math.OC)Control systemBounded functioncontinuous systemsPerpetual inventorycontinuous systems; linear matrix inequalities; linear systems; manufacturing systems; robust control; state feedback; stock control; uncertain systemsinventory controlRobust controlSettore MAT/09 - Ricerca Operativarobust controlimpulse control
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Least-Norm Regularization For Weak Two-Level Optimization Problems

1992

In this paper, we consider a regularization for weak two-level optimization problems by adaptation of the method presented by Solohovic (1970). Existence and approximation results are given in the case in which the constraints to the lower level problems are described by a multifunction. Convergence results for the least-norm regularization under perturbations are also presented.

Mathematical optimizationOptimization problemNorm (mathematics)Proximal gradient methods for learningRegularization perspectives on support vector machinesBackus–Gilbert methodRegularization (mathematics)Mathematics
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Approximation-Based Adaptive Fuzzy Tracking Control for a Class of Nonstrict-Feedback Stochastic Nonlinear Time-Delay Systems

2015

This paper focuses on the problem of approximation-based adaptive fuzzy tracking control for a class of stochastic nonlinear time-delay systems with a nonstrict-feedback structure. A variable separation approach is introduced to overcome the design difficulty from the nonstrict-feedback structure. Mamdani-type fuzzy logic systems are utilized to model the unknown nonlinear functions in the process of controller design, and an adaptive fuzzy tracking controller is systematically designed by using a backstepping technique. It is shown that the proposed controller guarantees that all signals in the closed-loop system are fourth-moment semiglobally uniformly ultimately bounded, and the tracking…

Mathematical optimizationStochastic processApplied MathematicsFuzzy logicTracking errorNonlinear systemComputational Theory and MathematicsArtificial IntelligenceControl and Systems EngineeringControl theoryBacksteppingAdaptive systemBounded functionMathematicsIEEE Transactions on Fuzzy Systems
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Solving dynamic memory allocation problems in embedded systems with parallel variable neighborhood search strategies

2015

International audience; Embedded systems have become an essential part of our lives, thanks to their evolution in the recent years, but the main drawback is their power consumption. This paper is focused on improving the memory allocation of embedded systems to reduce their power consumption. We propose a parallel variable neighborhood search algorithm for the dynamic memory allocation problem, and compare it with the state of the art. Computational results and statistical tests applied show that the proposed algorithm produces significantly better outcomes than the previous algorithm in shorter computing time.

Mathematical optimizationparallelismmetaheuristicsC dynamic memory allocationComputer sciencebusiness.industryApplied Mathematics[INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO]Static memory allocationPower consumptionEmbedded systemDiscrete Mathematics and Combinatoricsdynamic memory allocation problemembedded systemsState (computer science)businessMetaheuristicvariable neighborhood searchVariable neighborhood searchDrawbackStatistical hypothesis testing
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