Search results for "Discrete event simulation"

showing 10 items of 14 documents

Application of learning pallets for real-time scheduling by use of artificial neural network

2011

Author's version of a chapter in the book: 5th International Conference on Software, Knowledge Information, Industrial Management and Applications (SKIMA). Also available from the publisher at: http://dx.doi.org/10.1109/SKIMA.2011.6089986 Generally, this paper deals with the problem of autonomy in logistics. Specifically here, a complex problem in inbound logistics is considered as real-time scheduling in a stochastic shop floor problem. Recently, in order to comply with real-time decisions, autonomous logistic objects have been suggested as an alternative. Since pallets are common used objects in carrying materials (finished or semi-finished), so they have the possibility to undertake the …

EngineeringJob shop schedulingArtificial neural networkbusiness.industryVDP::Technology: 500Distributed objectManufacturing systemsIndustrial engineeringVDP::Mathematics and natural science: 400::Mathematics: 410Scheduling (computing)assembly systems learning neural networks real time systemsPalletOpen shopArtificial intelligenceDiscrete event simulationbusiness2011 5th International Conference on Software, Knowledge Information, Industrial Management and Applications (SKIMA) Proceedings
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A Fuzzy Discrete Event Simulator for Fuzzy Production Environment Analysis

1998

Abstract Discrete Event Simulation is a powerful tool to help production managers in planning manufacturing systems. The necessity to rapid react to market conditions is pushing production planners to process requirements and information affected by vagueness. Vagueness is related with event definition, therefore it is not manageable through statistical tools, but more properly by using fuzzy mathematics. Production situations where uncertainty takes body in term of vagueness are referred as Fuzzy Production Environments. Classical Discrete Event simulators are not suitable to deal with fuzzy variables, therefore they cannot be used to model Fuzzy Production Environments. This paper aims to…

EngineeringNeuro-fuzzyEvent (computing)business.industryMechanical EngineeringVaguenessFuzzy control systemFuzzy logicIndustrial and Manufacturing EngineeringFuzzy mathematicsFuzzy set operationsDiscrete event simulationbusinessSimulationCIRP Annals
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An Object-Oriented Approach to Discrete-Event Simulation Applied to Underground Railway Systems

1999

This paper describes the implementation of an object-oriented simulator that supports the determination of timetables and the design of on-line control policies for underground rail way systems. The simulator has been developed on the basis of a new approach to object- oriented modelling. Such an approach has been used to design a development tool that supports the generation of simulation codes and is able to automatically define the skeleton of a code.

EngineeringObject-oriented programming021103 operations researchDiscrete event systemBasis (linear algebra)business.industryDistributed computing0211 other engineering and technologies02 engineering and technologyObject (computer science)Computer Graphics and Computer-Aided DesignModeling and SimulationObject oriented simulationRail transportation0202 electrical engineering electronic engineering information engineeringUrban transportation020201 artificial intelligence & image processingDiscrete event simulationbusinessSoftwareSimulationSIMULATION
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Coordination policies to support decision making in distributed production planning

2003

Abstract Distributed production networks are considered organizational structures able to match agility and efficiency necessary to compete in the global market. Performances of such organization structures heavily depend on the ability of the network actors of coordinating their activities. The research proposes to model and design coordination problems within production network by using the Multiple Agent Technology. In particular, the paper proposes new strategies for coordinating production-planning activities within production networks. Such models have been developed and tested by using a proper simulation environment developed by using open source code and architecture. The results o…

EngineeringProcess managementKnowledge managementbusiness.industryGeneral MathematicsMulti-agent systemIndustrial and Manufacturing EngineeringComputer Science ApplicationsProduction planningControl and Systems EngineeringCode (cryptography)Production (economics)Organizational structureCoordination gameArchitectureDiscrete event simulationbusinessSoftwareRobotics and Computer-Integrated Manufacturing
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Cost Analysis of FMS Throughput

1988

Abstract The need for an effective cost planning and control system is stressed in today highly competitive manufacturing environment. The conventional approaches of machining economics to cost analysis are no more able to cope with the new structure of the production costs in the highly automated - highly integrated manufacturing systems. Suitable cost analysis procedures should provide a strong integration between process planning data and overall system performances. The here proposed procedure for the estimate of the unit manufacturing cost in FMSs achieves this integration by using performance evaluation techniques like discrete event simulation or queueing network models.

Engineeringbusiness.industryProcess (engineering)Mechanical EngineeringIndustrial and Manufacturing EngineeringManufacturing costManufacturing engineeringReliability engineeringMachiningComputer-integrated manufacturingControl systemProduction (economics)Discrete event simulationbusinessThroughput (business)CIRP Annals
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Fuzzy Discrete Event Simulation for Fuzzy Production Systems Analysis

1998

Abstract Fuzzy production systems are characterised by vagueness in data and requirements that very often cannot be reduced to stochastic models. Therefore, such production systems cannot be analysed by using classical techniques such as Queue Theory or Discrete Simulation Analysis. On the other hand the great diffusion of Fuzzy Production environments in small and medium enterprises claims for the development of new analysis tools. This paper proposes a new approach to Discrete Event Simulation able to treat with fuzzy variables. A new methodology has been proposed to process fuzzy information within discrete event simulation and a prototype of a Fuzzy Discrete Event Simulator has been dev…

Fuzzy electronicsFuzzy transportationNeuro-fuzzyStochastic modellingComputer scienceFuzzy set operationsFuzzy associative matrixControl engineeringFuzzy control systemDiscrete event simulationFuzzy logicDefuzzificationIFAC Proceedings Volumes
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IMPROVEMENTS IN THE SYSTEMS-BASED MODELS GENERATOR SIGEM

1994

Program generators, for us, are computer programs that produce other computer programs. SIGEM is an expert system program generator that can help in the modeling process of real systems. It is associated with a methodology well adapted to modeling practice. In this paper, we present and compare this methodology with other similar ones. Static models (databases), dynamic models, rule-based expert systems, literal and/or numerical variables, probabilistic uncertainty in data and in functions, dimensioned variables, discrete event simulation, and other related problems can be treated with this methodology. We suggest a systems modeling methodology and a programming tool to increase generality …

GeneralityGenerator (computer programming)Computer programComputer sciencebusiness.industryProcess (engineering)Probabilistic logicSystems modelingcomputer.software_genreIndustrial engineeringExpert systemArtificial IntelligenceArtificial intelligenceDiscrete event simulationbusinesscomputerSoftwareInformation SystemsCybernetics and Systems
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Advanced Stochastic Petri Net Modeling with the Mercury Scripting Language

2017

Formal models are widely used in performance and dependability studies of computational systems. Graphical modeling tools allow users to compose such models with ease, but they complicate the creation of models with a dynamic/complex structure, the hierarchical arrangement of different models, and the automatic execution of models with different parameter configurations. To overcome this problem, we created a scripting language for the Mercury tool that supports the combination of different modeling approaches (e.g., Stochastic Petri Nets and Reliability Block Diagrams) in a single project. In this paper, we focus on the extensions developed to improve the capabilities of Generalized Stocha…

Hierarchical modelingProgramming languageComputer science020206 networking & telecommunicationsReliability block diagram02 engineering and technologycomputer.software_genreScripting language0202 electrical engineering electronic engineering information engineeringStochastic Petri netDependability020201 artificial intelligence & image processingPhase-type distributionMercury (programming language)Discrete event simulationcomputercomputer.programming_languageProceedings of the 11th EAI International Conference on Performance Evaluation Methodologies and Tools
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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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Implementation and performance of the third level muon trigger of the ATLAS experiment at LHC

2006

The trigger system of the ATLAS experiment at the LHC aims at a high selectivity in order to keep the full physics potential while reducing the 40 MHz initial event rate imposed by the LHC bunch crossing down to /spl sim/100 Hz, as required by the data acquisition system. Algorithms working in the final stage of the trigger environment (Event Filter) are implemented to run both in a "wrapped" mode (reconstructing tracks in the entire Muon Spectrometer) and in a "seeded" mode (according to a dedicated strategy that performs pattern recognition only in regions of the detector where trigger hypotheses have been produced at earlier stages). The working principles of the offline muon reconstruct…

Nuclear and High Energy PhysicsParticle physicsHLTPhysics::Instrumentation and DetectorsMuonReal-time computingevent filter01 natural sciencesData acquisitionAtlas (anatomy)0103 physical sciences[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]medicineElectrical and Electronic EngineeringDiscrete event simulationDetectors and Experimental TechniquesPhysicsMuonsLarge Hadron Collider010308 nuclear & particles physicsEvent (computing)DetectorATLAS experimentMuons.ATLASTriggermedicine.anatomical_structureNuclear Energy and EngineeringFilter (video)Event Filter
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