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

共 418 条记录，以下是1-10 订阅

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

Proceedings of the 2013 Winter Simulation Conference - Simul...

引用

2013 43rd winter simulation conference - simulation: making decisions in a complex world, WSC 2013

ISBN: (纸本)9781479939503

The proceedings contain 346 papers. The topics discussed include: ARD: an automated replication-deletion method for simulation analysis;low-storage online estimators for quantiles and densities;linking statistical estimation and decision making through simulation;stochastic kriging with qualitative factors;density estimation of simulation output using exponential EPI-splines;have we really been analyzing terminating simulations incorrectly all these years?;on the solution of stochastic optimization problems in imperfect information regimes;robust selection of the best;ranking and selection in a high performance computing environment;the knowledge gradient algorithm using locally parametric approximations;adaptive simulation budget allocation for determining the best design;R-spline for local integer-ordered simulation optimization problems with stochastic constraints;and upper bounds on the Bayes-optimal procedure for ranking & selection with independent normal priors.

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A simulation-Infused Optimization Approach for Decomposing Nonlinear Systems 24

A Simulation-Infused Optimization Approach for Decomposing N...

引用

Proceedings of the winter simulation conference

作者： Zeyu Liu Dept. of Industrial and Mgmt. Systems Eng. West Virginia University Morgantown WV USA

ISBN: (纸本)9798331534202

With the rapid advancements in modern computing technologies, simulation has been increasingly adopted to model complex real-world systems. Yet, such digital computational power remains underutilized in decision-making tasks, mainly due to the difficulties in integrating gray or black box simulation models with algebraic optimization. In this study, we address this by proposing a novel and generic simulation-infused optimization approach. Through decomposition, nonlinear subsystems are surrogated by simulation and approximated by cutting planes in a row generation algorithm for holistic optimization. Exploration and exploitation are introduced to the row generation algorithm via a novel parametric method. The proposed simulation-infused decomposition approach is applied to a multi-depot vehicle routing problem. Proof-of-concept experiments are conducted to validate the performance against benchmarks, showing drastic reductions in computational time and improvements upon conventional optimization methods when real-world nonlinear systems are involved.

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Modeling of Agent decisions Using Conditional Generative Adversarial Networks 24

Modeling of Agent Decisions Using Conditional Generative Adv...

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Proceedings of the winter simulation conference

作者： Martin Bicher Dominik Brunmeir Niki Popper Institute for Information Systems Engineering TU Wien Vienna AUSTRIA Institute for Information Systems Engineering TU Wien Vienna AUSTRIA and dwh simulation services dwh GmbH Vienna AUSTRIA

ISBN: (纸本)9798331534202

In this paper, we investigate the use of Generative Adversarial Networks (GAN) to model agent behavior in agent-based models. We hereby focus on use cases in which an agent's decision-making process may only be modeled from data, but it is infeasible to be modeled causally. In these situations, meta-models are often the only way to quantitatively parameterize the agent-based model. However, methods that capture not only deterministic relationships but also stochastic uncertainty are rare. Since GANs are well known for their property to generate pseudo-random-numbers for complex distributions, we explore pros and cons of this strategy for modeling a delay-process in a large-scale agent-based SARS-CoV-2 simulation model.

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AI-Driven Physics-Based simulation Design with Optical Flow Based Markov Decision Processes for Smart Surveillance 24

AI-Driven Physics-Based Simulation Design with Optical Flow ...

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Proceedings of the winter simulation conference

作者： Seunghan Lee Yinwei Zhang Aaron LeGrand Seth Gibson-Todd Dept. of Industrial and Systems Engineering Mississippi State University Mississippi State MS USA Dept. of Systems and Industrial Engineering University of Arizona Tucson AZ USA

ISBN: (纸本)9798331534202

This paper presents an integrated approach to enhancing situational awareness and decision-making in dynamic environments by combining optical-flow-based Markov Decision Processes (MDP) with physics-based simulations for proactive surveillance system design. By utilizing optical flow for real-time motion detection and analysis, our framework achieves immediate comprehension of environmental changes, which is essential for autonomous navigation and surveillance applications. Additionally, the framework employs MDP to model and resolve decision-making problems where outcomes are partly random and partly controlled by the decision-maker, optimizing actions based on predicted future states. The model was validated through Hardware-in-the-loop (HITL) simulations, providing a detailed understanding of the physical phenomena influencing the system. This ensures that decisions are data-driven and customized to specific situations and missions. Our approach offers a comprehensive understanding of system integration with AI, along with real-time analysis and decision-making capabilities, thereby advancing the simulation modeling methodology for engaging with complex, dynamic environments.

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Smart Management of Dairy Farms Based on simulation 24

Smart Management of Dairy Farms Based on Simulation

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Proceedings of the winter simulation conference

作者： Osvaldo Palma Lluis M. Plà-Aragonés Alejandro Mac Cawley Víctor M. Albornoz Dept. of Economics and Administration Universidad Nacional Andrés Bello CHILE and Dept. of Mathematics Universidad de Lleida ESPAÑA Dept. of Mathematics Universidad de Lleida ESPAÑA Dept. of Industrial Eng. Pontificia Universidad Católica de Chile CHILE Dept. of Industrial Eng. Universidad Técnica Federico Santa María CHILE

ISBN: (纸本)9798331534202

Milk and beef production is crucial to ensure a cost-effective and sustainable food supply. As the demand for agricultural products increases, making informed decisions are critical. Discrete event simulation, a suitable tool for modeling many complex systems with random variability, offers substantial advantages compared with traditional analytical models. We developed a discrete event simulation model for a dairy herd. The model is shown useful for studying various culling strategies based on disease or reproductive performance. We perform a preliminary validation of the model by comparing steady state behavior to analytical results from a Markov chain model and literature. Our findings demonstrate that twin calving does not significantly affect herd performance. We advocate the use of discrete event simulation integrated in smart management tools, emphasizing its usefulness in decision-making on dairy farms. In future research, we are exploring additional factors such as abortion, mortality, and time variable periods for state variables.

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Simdiff: Modeling and Generation of Stochastic Discrete-Event simulation Inputs via Denoising Probabilistic Diffusion Process 24

Simdiff: Modeling and Generation of Stochastic Discrete-Even...

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Proceedings of the winter simulation conference

作者： Fengwei Jia Hongli Zhu Fengyuan Jia Xinyue Ren Siqi Chen Hongming Tan Wai Kin Victor Chan Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen CHINA Anhui Province Key Laboratory of Special Heavy Load Robot Maanshan Anhui CHINA

ISBN: (纸本)9798331534202

This paper introduces simulation using Diffusion process (SimDiff), a novel framework for automated modeling and generation of stochastic discrete-event simulation (DES) input distributions, addressing the high entry barrier and challenges associated with obtaining accurate input data. Traditional DES models often rely on simplifying assumptions, such as Poisson and Exponential distributions, which may not fully capture the complexity of real-world systems. We propose SimDiff to overcome these limitations by utilizing the denoising probabilistic diffusion model, a generative neural network capable of learning complex statistical distributions and efficiently sampling from them. Additionally, we introduce SimDiff-ConvTrans, an extension that incorporates Transformer and Convolution components for simulating non-i.i.d inputs. Our experiments demonstrate the effectiveness of SimDiff in handling simple and hybrid data distributions, as well as empirical datasets. SimDiff represents a significant advancement in simplifying the stochastic simulation process, making it more accessible and efficient for users across various expertise levels.

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simulation TRUST AND THE INTERNET OF THINGS

SIMULATION TRUST AND THE INTERNET OF THINGS

引用

winter simulation conference (WSC)

作者： Loper, Margaret L. Georgia Inst Technol Georgia Tech Res Inst Informat & Commun Lab Atlanta GA 30308 USA

ISBN: (纸本)9781728132839

The urban environment is becoming increasingly more connected and complex. In the coming decades, we will be surrounded by billions of sensors, devices, and machines, the Internet of Things (IoT). As the world becomes more connected, we will become dependent on machines and simulation to make decisions on our behalf. When simulation systems use data from sensors, devices and machines (i.e., things) to make decisions, they need to learn how to trust that data, as well as the things they are interacting with. As embedded simulation becomes more commonplace in IoT and smart city applications, it is essential that decision makers are able to trust the simulation systems making decisions on their behalf. This paper looks at trust from an IoT perspective, describing a set of research projects conducted that span multiple dimensions of trust, and discusses whether these concepts of trust apply to simulation.

关键词： Internet of things

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LINKING STATISTICAL ESTIMATION AND DECISION making THROUGH simulation

LINKING STATISTICAL ESTIMATION AND DECISION MAKING THROUGH S...

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winter simulation conference on simulation - making decisions in a complex world

作者： Fang, Jin Hong, L. Jeff Hong Kong Univ Sci & Technol Dept Ind Engn & Logist Management Kowloon Hong Kong Peoples R China

ISBN: (纸本)9781479939503;9781479920778

Models that are built to help make decisions usually involve input parameters, which need to be estimated statistically using data. However, submitting these estimated parameters directly to the model may result in biased decisions because the estimated parameters are biased or the model is nonlinear. We propose a new parameter estimator called simulation-Based Inverse Estimator (SBIE) to link the statistical estimation and decision making together. The linkage is achieved by simulating the model and adjusting the estimated parameters such that the adjusted parameters can adapt to the specific model. We prove that SBIE can provide us with consistent and unbiased decisions under some conditions and this result is supported by numerical experiments in queuing models.

关键词： Adaptation models Biological system modeling Data models Maximum likelihood estimation Monte Carlo methods Numerical models

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DESIGNING simulation EXPERIMENTS

DESIGNING SIMULATION EXPERIMENTS

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winter simulation conference on simulation - making decisions in a complex world

作者： Barton, Russell R. Penn State Univ Dept Supply Chain & Informat Syst University Pk PA 16802 USA

ISBN: (纸本)9781479939503;9781479920778

Much effort goes into building and validating simulation models. Similar care is necessary in the use of the model to support decision making. Good simulation experiment design is important to get useful and valid insights for specific management questions. This introductory tutorial gives an overview of experiment design techniques for justifying and planning a series of simulation runs to uncover the impact of system design parameters on simulation output performance. Graphical methods are emphasized.

关键词： Decision making Feeds Machine shops Maintenance engineering Predictive models Throughput Tutorials

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A HEURISTIC TO SUPPORT MAKE-TO-STOCK, ASSEMBLE-TO-ORDER, AND MAKE-TO-ORDER decisions IN SEMICONDUCTOR SUPPLY CHAINS

A HEURISTIC TO SUPPORT MAKE-TO-STOCK, ASSEMBLE-TO-ORDER, AND...

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winter simulation conference on simulation - making decisions in a complex world

作者： Forstner, Lisa Moench, Lars Infineon Technol AG Supply Chain Management Campeon 1-12 D-85579 Neubiberg Germany Univ Hagen Dept Math & Comp Sci D-58037 Hagen Germany

ISBN: (纸本)9781479939503;9781479920778

In this paper, we study Make-to-stock, Assemble-to-order, and Make-to-order decisions in semiconductor supply chains. We propose a genetic algorithm to support such decisions. Discrete-event simulation is used to estimate the profit-based objective function taking into account the stochastic behavior of the supply chain. We perform computational experiments with a simplified semiconductor supply chain model. It is shown that the proposed heuristic outperforms simple partitioning heuristics based on product characteristics.

关键词： Discrete event simulation

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