simulation performance may be evaluated according to multiple quality measures that are in competition and their simultaneous consideration poses a conflict. In the current study we propose a practical framework for i...
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ISBN:
(纸本)9781479939503;9781479920778
simulation performance may be evaluated according to multiple quality measures that are in competition and their simultaneous consideration poses a conflict. In the current study we propose a practical framework for investigating such simulation performance criteria, exploring the inherent conflicts amongst them and identifying the best available tradeoffs, based upon multiobjective Pareto optimization. This approach necessitates the rigorous derivation of performance criteria to serve as objective functions and undergo vector optimization. We demonstrate the effectiveness of our proposed approach by applying it to a specific Artificial Neural Networks (ANN) simulation, with multiple stochastic quality measures. We formulate performance criteria of this use-case, pose an optimization problem, and solve it by means of a simulation-based Pareto approach. Upon attainment of the underlying Pareto Frontier, we analyze it and prescribe preference-dependent configurations for the optimal simulation training.
Discrete event simulation (DES) is a technique used extensively and effectively by large companies, however it is not widely used by small to medium sized enterprises (SMEs) due to complexity and related costs being p...
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ISBN:
(纸本)9781479939503;9781479920778
Discrete event simulation (DES) is a technique used extensively and effectively by large companies, however it is not widely used by small to medium sized enterprises (SMEs) due to complexity and related costs being prohibitively high. In SMEs, DES-related data can be stored in a variety of formats and it is not always evident what data is required (if even available) to support a DES model in relation to specific problem scenarios. Therefore the DES data gathering and preparation phase is where complexity and effort required are highest in order to avoid the potential for erroneous results due to incorrect assumed or real input data. The proposed solution is a Cloud-based adapter that can identify and connect to existing data sources and/or fills gaps in data in relation to defined problem scenarios, thus lowering the barriers for SMEs to gain benefit from DES studies due to reduced complexity and effort.
Information shared through online social networking platforms is spread from user to user. Although some researchers have argued that this phenomenon can unfold similarly to an epidemic, others have found that informa...
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ISBN:
(纸本)9781479939503;9781479920778
Information shared through online social networking platforms is spread from user to user. Although some researchers have argued that this phenomenon can unfold similarly to an epidemic, others have found that information disseminates within a narrow range, propagating only a few levels in a communication network. In an effort to resolve these conflicting findings, we developed an information cascade model to conduct a variance-based global sensitivity analysis (GSA) to determine the influence of two network attributes on the diffusion of energy saving information. The simulation results of the base model showed that energy saving information failed to generate deep cascades. Also, the results from the GSA demonstrated that network density and the number of an initiator's connections had limited influence on information cascades. These findings suggest that massive network structures and a large number of potential recipients do not engender deep cascades of energy saving information in online social networks.
In the modern manufacturing industry, environmental considerations are part of numerous phases of production. Inappropriate production lot-size determination can generate substantial scrapped overdue stocks and idle p...
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ISBN:
(纸本)9781479939503;9781479920778
In the modern manufacturing industry, environmental considerations are part of numerous phases of production. Inappropriate production lot-size determination can generate substantial scrapped overdue stocks and idle processing, which lead to serious environmental burdens. In this paper, by simulating the Pull mode and back scheduling of a multi-variety and small-batch production system, large overstocks and other wastes caused by current production lot-size determination are traced. For comparison with the conventional cost accounting used in the original simulation model, a new environmental management accounting method, Material Flow Cost Accounting (MFCA), is introduced to identify negative products cost related to environmental impacts hidden in the production processes. After sensitivity analysis by gradually regulating the production lot-size, two regular changes in the negative products cost and the corresponding percentages in the total cost are observed. These change trends indicate that a reasonable determination strategy for production lot-size can improve both economic and environmental performances.
This paper discusses the development of an individual based simulation model for evaluation of interventions for better treatment of patients with abdominal aortic aneurysms (AAA). The interdisciplinary subject requir...
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ISBN:
(纸本)9781479939503;9781479920778
This paper discusses the development of an individual based simulation model for evaluation of interventions for better treatment of patients with abdominal aortic aneurysms (AAA). The interdisciplinary subject required collaboration of medical doctors, Health Technology Assessment (HTA) experts and modelers. The here presented modular model structure is flexible enough to allow adaptation on screening research questions for similar diseases. Another focus of the work was integration of risk factors and how it determines our model choice, especially because steadily increasing knowledge about or improved treatment of AAA could cause necessity of reevaluation. Through inclusion of several patient specific properties the model does not only provide comparison of current state with screening but also elaboration of alterations of population characteristics and its consequences on AAA cases.
When fitting queueing models to service system data, it can be helpful to perform statistical tests to confirm that the candidate model is appropriate. The Kolmogorov- Smirnov (KS) test can be used to test whether a s...
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ISBN:
(纸本)9781479939503;9781479920778
When fitting queueing models to service system data, it can be helpful to perform statistical tests to confirm that the candidate model is appropriate. The Kolmogorov- Smirnov (KS) test can be used to test whether a sample of interarrival times or service times can be regarded as a sequence of i.i.d. random variables with a continuous cdf, and also to test a nonhomogeneous Poisson Process (NHPP). Using extensive simulation experiments, we study the power of various alternative KS tests based on data transformations. Among available alternative tests, we find the one with the greatest power in testing a NHPP. Furthermore, we devise a new method to test a sequence of i.i.d. random variables with a specified continuous cdf;it first transforms a given sequence to a rate-1 Poisson process (PP) and then applies the existing KS test of a PP. We show that it has greater power than direct KS tests.
Traditional instruction and information delivery methods, as well as memorization are still largely considered the cornerstones of STEM education. Meanwhile, a growing number of students exhibits strong tendency towar...
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ISBN:
(纸本)9781479939503;9781479920778
Traditional instruction and information delivery methods, as well as memorization are still largely considered the cornerstones of STEM education. Meanwhile, a growing number of students exhibits strong tendency toward technology-based student-centered learning. It is thus imperative that if instructors do not keep up with the pace of technology, soon they will not be able to properly teach students how to effectively work in collaborative and invigorating settings. This paper reports on the findings of an ongoing research that aims at incorporating mobile context-aware visual simulation into STEM education. So far, the authors have used construction and civil engineering as a test bed and developed a mobile augmented reality (AR) visualization platform that allows students to: (1) enhance the contents of their textbooks with computer-generated virtual multimedia and graphics, and (2) interact with context-aware simulated animations. The developed methods have been successfully tested in classroomscale experiments using real student populations.
We use Gaussian random fields (GRFs) that we call generalized integrated Brownian fields (GIBFs), whose covariance functions have been studied in the context of reproducing kernels, for Gaussian process modeling. We i...
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ISBN:
(纸本)9781479939503;9781479920778
We use Gaussian random fields (GRFs) that we call generalized integrated Brownian fields (GIBFs), whose covariance functions have been studied in the context of reproducing kernels, for Gaussian process modeling. We introduce GIBFs into the fields of deterministic and stochastic simulation metamodeling, and give a probabilistic representation of GIBFs that is not given in the literature on reproducing kernels. These GIBFs have differentiability that can be controlled in each coordinate, and are built from GRFs which have the Markov property. Furthermore, we introduce a new parameterization of GIBFs which allows them to be used in higher-dimensional metamodeling problems. We also show how to implement stochastic kriging with GIBFs, covering trend modeling and fitting. Lastly, we use tractable examples to demonstrate superior prediction ability as compared to the GRF corresponding to the Gaussian covariance function.
This paper introduces Simulus, a full-fledged open-source discrete-event simulator, supporting both event-driven and process-oriented simulationworld-views. Simulus is implemented in Python and aspires to be a part o...
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ISBN:
(纸本)9781728194998
This paper introduces Simulus, a full-fledged open-source discrete-event simulator, supporting both event-driven and process-oriented simulationworld-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, inter-process 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.
Increasing variety and complexity of products in existing semiconductor factories cause an increased amount of production steps. Accordingly, this leads to a significant increase of non value added transportation proc...
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ISBN:
(纸本)9781479939503;9781479920778
Increasing variety and complexity of products in existing semiconductor factories cause an increased amount of production steps. Accordingly, this leads to a significant increase of non value added transportation processes. Therefore, transport and storage durations shall be minimized by optimal alteration of the given automated material handling system (AMHS). This can be achieved by simulation and analysis of possible AMHS alterations. However, this is a difficult task because of the system's complexity, the large amount of data and the high effort of manually modifying and testing many different AMHS alterations. In order to assist the system experts in executing these tasks, the authors suggest a method for automatic planning, execution and comparison of simulation experiments, including the automatic alteration of the transportation system's layout by introducing additional AMHS segments as shortcuts. The approach is feasible for existing simulation models as well as for generating simulations from the factory's core data.
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