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检索条件"任意字段=Winter Simulation Conference on Simulation - Making Decisions in a Complex World"

共 419 条记录，以下是361-370 订阅

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Combining simulation and integer programming IP techniques to achieve realistic optimality 13

Combining simulation and integer programming IP techniques t...

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Proceedings of the 2013 winter simulation conference: simulation: making decisions in a complex world

作者： Ahmed A. Elfituri Andy W. Lung Kingston University London UK

ISBN: (纸本)9781479920778

In recent years, call centers have been considered as an integral part of the modern businesses. High performance of call centers, therefore, is crucial to ensure high level of customer satisfaction in today's competitive market. In order to achieve that high performance, managers of call centers face a very difficult set of challenges. They need to achieve low operating costs and high service quality. The proposed framework combines statistical, simulation, and integer programming (IP) techniques in achieving realistic optimality. The framework begins by developing stochastic statistical data models for call center operations parameters which are divided into service demand (arrival volumes) and service quality (service times, abandonment volumes, and patience time) parameters. These data models are then used to run a simulation model that is used to determine the minimum staffing levels in daily, hour periods. Finally, these staffing levels are considered as input to an IP model that optimally allocates the service agents to the different operating shifts of the working day.

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Print production designer: answering commercial/industrial print production what-ifs using simulation-as-a-service 13

Print production designer: answering commercial/industrial p...

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Proceedings of the 2013 winter simulation conference: simulation: making decisions in a complex world

作者： Sunil Kothari Jun Zeng Gary Dispoto Hewlett-Packard

ISBN: (纸本)9781479920778

Service level forecasting and capacity planning is uniquely challenging in commercial and industrial print service providers (PSPs) due to: 1) Large variations in supply and demand. Diverse service requests arrive stochastically; production processes heavily rely on manual work, are fault-prone and weakly structured. 2) Little or no factory audit data. Most PSPs do not have means to track production events. 3) Lack of affordable modeling tools and expertise. Many tools cost thousands of dollars and require simulation experts to spend weeks on customer sites. We developed Print Production Designer (PPD) to attack the aforementioned challenges. Powered by a custom factory dynamics simulation engine based on UC Berkeley's Ptolemy toolkit and deployed as a cloud service, PPD brings quantitative trade-offs to light, optimizes customers' information, and helps them to reach the right printing press purchasing decision. A typical PPD run costs $5.28 which is affordable for even small-sized PSPs.

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Projecting prison populations with SAS® simulation studio 13

Projecting prison populations with SAS® simulation studio

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Proceedings of the 2013 winter simulation conference: simulation: making decisions in a complex world

作者： Jeffrey D. Day Bahadir Aral Emily Lada Ginny M. Hevener Tamara R. Flinchum SAS Institute North Carolina Sentencing and Policy Advisory Commission

ISBN: (纸本)9781479920778

The majority of the states in the USA have a process to project prison populations for the purpose of planning adequate capacity. Typical time series methods are ineffective because they do not take into account factors like sentence length, prior criminal history, revocations of community supervision, and legislative changes. Discrete event simulation has proven to be a viable alternative. The North Carolina Sentencing and Policy Advisory Commission collaborated with SAS to build a model in SAS simulation Studio that projects the number of prison beds needed for the next ten years. The model uses current prison population data, recent court convictions, revocations of community supervision, and estimates of growth to play out the admissions and releases of inmates over the time horizon of the model. The prison projections are updated by the Sentencing Commission on an annual basis.

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A Gaussian Process Based Algorithm for Stochastic simulation Optimization with Input Distribution Uncertainty

A Gaussian Process Based Algorithm for Stochastic Simulation...

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simulation winter conference

作者： Haowei Wang Szu Hui Ng Xun Zhang National University of Singapore Singapore SINGAPORE

ISBN: (数字)9781728194998

ISBN: (纸本)9781728195001

Stochastic simulation models are increasingly popular for analyzing complex stochastic systems. However, the input distributions driving the simulation models are typically unknown in practice and are usually estimated from real world data. Since the size of real world data tends to be limited, the resulting estimation of input distribution will contain errors. This estimation error is commonly known as input uncertainty. In this paper, we consider the stochastic simulation optimization problem when the input uncertainty is present and assume that both the family and parameters of the input distribution are unknown. Traditional efficient metamodel-based optimization approaches like Efficient Global Optimization (EGO) do not take the input uncertainty into account. This can lead to sub-optimal decisions when the input uncertainty level is high. Here, we adopt a nonparametric Bayesian approach to model the input uncertainty and propose an EGO-based simulation optimization algorithm that explicitly accounts for the input uncertainty.

关键词： Analytical models Uncertainty Stochastic systems Approximation algorithms Data models Bayes methods Optimization

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Challenges in Modeling and Unmodeling complex Reactive Systems: Interaction Networks, Reaction to Emergent Effects, Reactive Rule Composition, and Multiple Time Scales 11th

Challenges in Modeling and Unmodeling Complex Reactive Syste...

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11th International conference on Model-Driven Engineering and Software Development (MODELSWARD)

作者： Marron, Assaf Cohen, Irun R. Frankel, Guy Harel, David Szekely, Smadar Weizmann Inst Sci Dept Comp Sci & Appl Math IL-76100 Rehovot Israel Weizmann Inst Sci Dept Immunol & Regenerat Biol IL-76100 Rehovot Israel

ISBN: (纸本)9783031663383;9783031663390

Models are central to the study of complex systems, both human-made and natural. They assist in making important decisions with regard to design and development of systems, and in planning a variety of actions in areas of everyday life, economy, the environment and more;and models are, of course, an essential element of scientific research. We examine several inherent difficult-to-implement requirements common to many models of complex systems that are part of, or work in, the real world. In this paper we describe the challenges associated with the following aspects of modeling complex systems: (i) complex real-world systems are exposed to an unbounded number of external and internal inputs and stimuli, and in reacting to such triggers, the system engages in a two-way interaction with its environment and with each of the particular sources of these inputs. (ii) New patterns, new relationships and, indeed, new entities, continually emerge, and the system manifests emergent reaction to these group effects. (iii) Either by human design, or by underlying laws of nature, complex cohesive system behavior often manifests the composite effects of separate, parallel, self standing requirements or natural phenomena that are integrated subject to some universal composition principles. (iv) Events and processes in such a system occur, or exist, on distinct time scales. We describe each of these challenges, propose concrete guidelines in modeling that can help cope with them, and outline directions for relevant features in modeling tools. An important element in dealing with these obstacles is unmodeling-explicitly documenting and specifying model elements that are excluded from simulations and model transformation for a variety of reasons. Such unmodeling enhances model quality, supports incremental enhancement, and facilitates evaluation of the model. This paper is one of the outcomes of a combined view of our research on modeling languages and our research on biological evolu

关键词： Modeling simulation Emergent entities Rule-based specifications Incremental development Evolution Time scale

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Independent verification & validation of integrated supply-chain network simulation and optimization models 13

Independent verification & validation of integrated supply-c...

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Proceedings of the 2013 winter simulation conference: simulation: making decisions in a complex world

作者： Soroosh Gholami Hessam Sarjoughian Gary Godding Victor Chang Daniel Peters ASU Intel Corporation

ISBN: (纸本)9781479920778

In this joint ASU/Intel research, we are undertaking Independent Verification & Validation (IV&V) of discrete-event and linear programming models developed in commercial simulation and optimization tools. These models are aimed at reproducing/predicting uncertainties across process-chains, suppliers, and consumers of prototypical Supply-Chain Networks (SNM). To achieve IV&V for SNMs, first we extended our DEVS process-chain models in the DEVS-Suite simulator. These models are constructed and executed using data contained in a realistic database. This allows comparing queuing-based vs. system-theoretic (DEVS) simulation modeling approaches and tools. Second, we integrated the optimization model with the DEVS model. At this stage, we validate state and control data exchanges between the simulation and optimization models. This effort leads to extending our integrated DEVS and Opl-Studio/CPLEX platform with a Knowledge Interchange Broker where interactions between simulation and optimization models are scalable and can also be independently mediated. Key findings of this industrial-scale IV&V development are exemplified.

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Factory flow design and analysis using internet-enabled simulation-based optimization and automatic model generation 11

Factory flow design and analysis using internet-enabled simu...

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simulation winter conference

作者： Amos H.C. Ng Jacob Bernedixen Matias Urenda Moris Mats Jägstam Virtual Systems Research Centre University of Skövde Skovde Sweden

Despite simulation offers tremendous promise for designing and analyzing complex production systems, manufacturing industry has been less successful in using it as a decision support tool, especially in the early conceptual phase of factory flow design. If simulation is used today for system design, it is more of-ten used in later phases when important design decisions have already been made and costs are locked. With an aim to advocate the use of simulation in early phases of factory design and analysis, this paper introduces FACTS Analyzer, a toolset developed based on the concept of integrating model abstraction, automatic model generation and simulation-based optimization under an innovative Internet-based plat-form. Specifically, it addresses a novel model aggregation and generation method, which when combined together with other system components, like optimization engines, can synthetically enable simulation to become much easier to use and speed up the time-consuming model building, experimentation and optimization processes, in order to support optimal decision making.

关键词： Optimization Analytical models Computational modeling Servers Object oriented modeling Data models Internet

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DYANA: HLA-based distributed real-time embedded systems simulation tool 13

DYANA: HLA-based distributed real-time embedded systems simu...

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Proceedings of the 2013 winter simulation conference: simulation: making decisions in a complex world

作者： Vitaly A. Antonenko Evgeny V. Chemeritskiy Alevtina B. Glonina Igor V. Konnov Vasily N. Pashkov Vladislav V. Podymov Konstantin O. Savenkov Ruslan L. Smeliansky Dmitry Yu. Volkanov Vladimir A. Zakharov Daniil A. Zorin Lomonosov Moscow State University Moscow Russia Vienna University of Technology Vienna Austria

ISBN: (纸本)9781479920778

In this paper we present DYANA, an HLA-based hardware-in-the-loop simulation tool. This tool is used for distributed Real-Time Embedded Systems (RTES) simulation. RTES models are described by Unified Modeling Language (UML) statechart diagrams. The statechart diagram is transformed into HLA-based simulation Model (HSM). After translation into HSM we use CERTI as the simulation runtime. The statechart diagram is also transformed into a Network of Timed Automata (NTA). After translation into NTA we use UPPAAL for RTES model verification.

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Simulus: Easy Breezy simulation in Python

Simulus: Easy Breezy Simulation in Python

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simulation winter conference

作者： Jason Liu School of Computing and Information Sciences Florida International University Miami Florida USA

ISBN: (数字)9781728194998

ISBN: (纸本)9781728195001

This paper introduces Simulus, a full-fledged open-source discrete-event simulator, supporting both event-driven and process-oriented simulation world-views. Simulus is implemented in Python and aspires to be a part of the Python's ecosystem supporting scientific computing. Simulus also provides several advanced modeling constructs to ease common simulation tasks (e.g., complex queuing models, interprocess synchronizations, and message-passing communications). Simulus also provides organic support for simultaneously running a time-synchronized group of simulators, either sequentially or in parallel, thereby allowing composable simulation of individual simulators handling different aspects of a target system, and enabling large-scale simulation running on parallel computers. This paper describes the salient features of Simulus and examines its major design decisions.

关键词： Analytical models Computational modeling Biological system modeling Transportation Predictive models Data models Mathematical model

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simulation models of forest resource management 77

Simulation models of forest resource management

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Proceedings of the 9th conference on winter simulation - Volume 2

作者： Dieter R. Pelz

The management of forest land for the simultaneous production of timber, recreational opportunities, wildlife food and habitat, and watershed protection requires complex decisions. simulation models formulated as decision aids or training tools in forest resources management are reviewed, ranging from strictly timber production models to multiple forest use models. The Illinois multiple forest use model was developed to aid the forest manager in his decision making. Alternative management strategies and their effects on the entire forest system can be evaluated with the model. The model is being validated for a private forest and a State Forest in Illinois.

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