Search results for "Turing"

showing 10 items of 2644 documents

Large multiple neighborhood search for the clustered vehicle-routing problem

2018

Abstract The clustered vehicle-routing problem is a variant of the classical capacitated vehicle-routing problem in which customers are partitioned into clusters, and it is assumed that each cluster must have been served completely before the next cluster is served. This decomposes the problem into three subproblems, i.e., the assignment of clusters to routes, the routing inside each cluster, and the sequencing of the clusters in the routes. The second task requires the solution of several Hamiltonian path problems, one for each possibility to route through the cluster. We pre-compute the Hamiltonian paths for every pair of customers of each cluster. We present a large multiple neighborhood…

Mathematical optimizationSequence021103 operations researchInformation Systems and ManagementGeneral Computer ScienceGeneralization0211 other engineering and technologies02 engineering and technologyManagement Science and Operations ResearchHamiltonian pathIndustrial and Manufacturing EngineeringTask (computing)symbols.namesakeComputingMethodologies_PATTERNRECOGNITIONModeling and SimulationVehicle routing problem0202 electrical engineering electronic engineering information engineeringsymbolsCluster (physics)020201 artificial intelligence & image processingRouting (electronic design automation)Hamiltonian (control theory)MathematicsEuropean Journal of Operational Research
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A comparison of column-generation approaches to the Synchronized Pickup and Delivery Problem

2015

Abstract In the Synchronized Pickup and Delivery Problem (SPDP), user-specified transportation requests from origin to destination points have to be serviced by a fleet of homogeneous vehicles. The task is to find a set of minimum-cost routes satisfying pairing and precedence, capacities, and time windows. Additionally, temporal synchronization constraints couple the service times at the pickup and delivery locations of the customer requests in the following way: a request has to be delivered within prespecified minimum and maximum time lags (called ride times) after it has been picked up. The presence of these ride-time constraints severely complicates the subproblem of the natural column-…

Mathematical optimizationService (systems architecture)Information Systems and ManagementGeneral Computer ScienceComputer scienceManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringSet (abstract data type)Task (computing)Modeling and SimulationVehicle routing problemPickupColumn generationInteger (computer science)European Journal of Operational Research
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On the evaluation of the global heat transfer coefficient in cutting

2007

The use of numerical simulations for investigating machining processes is remarkably increasing because of the simulation cost is lower than the experiments and the possibility to analyze local variables such as pressures, strains, and temperatures is allowable. Process simulation is very hard from a computational point of view, since it frequently requires remeshing phases and very small time steps. As a consequence, the simulated cutting time is usually of the order of few milliseconds and no steady cutting conditions are generally achieved, at least as far as thermal conditions are concerned. Therefore, nowadays numerical prediction of cutting temperatures cannot be considered fully reli…

Mathematical optimizationSteady stateMechanical EngineeringRakeMODELSMechanicsHeat transfer coefficientPressure coefficientIndustrial and Manufacturing EngineeringFinite element methodTOOL WEARMachiningTEMPERATURE DISTRIBUTIONHeat transferSIMULATIONProcess simulationFINITE-ELEMENT-ANALYSISSettore ING-IND/16 - Tecnologie E Sistemi Di LavorazioneMathematics
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Average flow constraints and stabilizability in uncertain production-distribution systems

2009

We consider a multi-inventory system with controlled flows and uncertain demands (disturbances) bounded within assigned compact sets. The system is modelled as a first-order one integrating the discrepancy between controlled flows and demands at different sites/nodes. Thus, the buffer levels at the nodes represent the system state. Given a long-term average demand, we are interested in a control strategy that satisfies just one of two requirements: (i) meeting any possible demand at each time (worst case stability) or (ii) achieving a predefined flow in the average (average flow constraints). Necessary and sufficient conditions for the achievement of both goals have been proposed by the aut…

Mathematical optimizationStochastic stabilityControl and OptimizationComputer scienceSCHEDULING POLICIESUNKNOWN INPUTSInventory control; Robust controlRobust controlUncertain systemsUncertain demandsManagement Science and Operations ResearchControl strategies; Inventory systems; Uncertain demands; Worst caseStability (probability)Distribution systemMULTI-INVENTORY SYSTEMSControl theoryProduction (economics)Inventory control Robust control Stochastic stabilityAverage costInventory systemsMathematicsInventory controlStochastic processControl strategiesApplied MathematicsWorst caseNETWORKSControllabilityFlow (mathematics)Bounded functionProduction controlRobust controlSettore MAT/09 - Ricerca OperativaMANUFACTURING SYSTEMS
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Methodological Approach to Studying the dynamics of production networks: a Discrete Event Simulation Model

2013

This paper shows how discrete-event simulation represents an appropriate tool for approaching the dynamics of production networks. Three important factors influencing production network dynamics, specifically finite production capacity, manufacturing lead time, and its variability are discussed and a basic discrete-event simulation model is presented. Such model, which in its basic form represents a simple retail/distribution two-stage supply chain, is then extended in order to take into account those factors that can not be included in a classical control theoretical model.

Mathematical optimizationSupply chain dynamicsInformation Systems and ManagementOperations researchComputer scienceSupply chainDemand amplificationManufacturing lead-timeControl (management)Management Science and Operations ResearchNetwork dynamicsSettore ING-IND/35 - Ingegneria Economico-GestionaleManagement Information SystemsOrder (exchange)Simple (abstract algebra)Production (economics)Discrete-event simulationDiscrete event simulationLead time
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Decision-aid for discrete multiple criteria decision making problems with imprecise data

1999

Abstract We describe ways of aiding decision making with a discrete set of alternatives. In many decision situations, it is not possible to obtain explicit preference information from the decision makers. Instead, useful decision-aid can be provided to the decision makers by describing what kind of weighting of the criteria result in certain choices of the alternatives. The suggested treatment is based on the basic ideas of the ELECTRE III method. The modelling of the preferences by pseudo-criteria is especially helpful in case the data, that is, the criterion values are imprecise. Unlike ELECTRE III, no ranking of the alternatives is produced. Based on a minimum-procedure in the exploitati…

Mathematical optimizationWeighted sum modelInformation Systems and ManagementGeneral Computer ScienceWeighted product modelEvidential reasoning approachDecision ruleManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringModeling and SimulationInfluence diagramELECTREOptimal decisionMathematicsDecision analysisEuropean Journal of Operational Research
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Solving the pentahedron problem

2015

Nowadays, all geometric modelers provide some tools for specifying geometric constraints. The 3D pentahedron problem is an example of a 3D Geometric Constraint Solving Problem (GCSP), composed of six vertices, nine edges, five faces (two triangles and three quadrilaterals), and defined by the lengths of its edges and the planarity of its quadrilateral faces. This problem seems to be the simplest non-trivial problem, as the methods used to solve the Stewart platform or octahedron problem fail to solve it. The naive algebraic formulation of the pentahedron yields an under-constrained system of twelve equations in eighteen unknowns. Even if the use of placement rules transforms the pentahedron…

Mathematical optimization[ INFO ] Computer Science [cs]Interval (mathematics)[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]Industrial and Manufacturing EngineeringDesargues’ theoremPolyhedronAl-Kashi theorem[INFO]Computer Science [cs]Algebraic numberFinite setMathematicsGeometric constraint solving problemsQuadrilateralGeometric modeling with constraintsSolution set[ MATH.MATH-NA ] Mathematics [math]/Numerical Analysis [math.NA]SolverComputer Graphics and Computer-Aided DesignPentahedronPentahedronComputer Science ApplicationsAlgebraInterval solver[ INFO.INFO-CG ] Computer Science [cs]/Computational Geometry [cs.CG][MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA]
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Designing Paper Machine Headbox Using GA

2003

Abstract A non-smooth biobjective optimization problem for designing the shape of a slice channel in a paper machine headbox is described. The conflicting goals defining the optimization problem are the ones determining important quality properties of produced paper: 1) basis weight should be even and 2) the wood fibers of paper should mainly be oriented to the machine direction across the width of the whole paper machine. The novelty of the considered approach is that maximum deviations are used instead of least squares when objective functions are formed. For the solution of this problem, a multiobjective genetic algorithm based on nondominated sorting is considered. The numerical results…

Mathematical optimizationbusiness.product_categoryOptimization problemBasis (linear algebra)Mechanical EngineeringSortingMulti-objective optimizationLeast squaresIndustrial and Manufacturing EngineeringPaper machineMechanics of MaterialsGenetic algorithmGeneral Materials SciencebusinessMathematicsCommunication channelMaterials and Manufacturing Processes
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Resource-constrained project scheduling: A critical activity reordering heuristic

2003

Abstract In this paper, we present a new metaheuristic algorithm for the resource-constrained project-scheduling problem. The procedure is a non-standard implementation of fundamental concepts of tabu search without explicitly using memory structures embedded in a population-based framework. The procedure makes use of a fan search strategy to intensify the search, whereas a strategic oscillation mechanism loosely related to the forward/backward technique provides the necessary diversification. Our implementation employs the topological order (TO) representation of schedules. To explore the TO vector space we introduce three types of moves, two of them based on the concept of relative critic…

Mathematical optimizationeducation.field_of_studyScheduleInformation Systems and ManagementGeneral Computer ScienceHeuristicComputer scienceHeuristic (computer science)PopulationManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringTabu searchModeling and SimulationFeature (machine learning)Guided Local SearcheducationRepresentation (mathematics)HeuristicsMetaheuristicEuropean Journal of Operational Research
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Robotic path planning for non-destructive testing – A custom MATLAB toolbox approach

2016

AbstractThe requirement to increase inspection speeds for non-destructive testing (NDT) of composite aerospace parts is common to many manufacturers. The prevalence of complex curved surfaces in the industry provides motivation for the use of 6 axis robots in these inspections. The purpose of this paper is to present work undertaken for the development of a KUKA robot manipulator based automated NDT system. A new software solution is presented that enables flexible trajectory planning to be accomplished for the inspection of complex curved surfaces often encountered in engineering production. The techniques and issues associated with conventional manual inspection techniques and automated s…

Mathematics(all)0209 industrial biotechnologyEngineeringTKGeneral Mathematics02 engineering and technologycomputer.software_genre01 natural sciencesIndustrial and Manufacturing EngineeringSettore ING-IND/14 - Progettazione Meccanica E Costruzione Di Macchine020901 industrial engineering & automationSoftwareAutomated non-destructive inspectionsNondestructive testingObstacle avoidancePath-planningComputer Aided DesignMotion planningSimulationbusiness.industry010401 analytical chemistryRoboticsAutomation0104 chemical sciencesComputer Science ApplicationsControl and Systems EngineeringTrajectoryRobotbusinesscomputerSoftwareRobotics and Computer-Integrated Manufacturing
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