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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381-390 订阅

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Smart Management of Dairy Farms Based on simulation

Smart Management of Dairy Farms Based on Simulation

引用

simulation winter 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 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: (数字)9798331534202

ISBN: (纸本)9798331534219

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.

关键词： Economics Analytical models Dairy products Decision making Mortality Production Cows Discrete event simulation Steady-state Diseases

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The role of simulation in planning 87

The role of simulation in planning

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Proceedings of the 19th conference on winter simulation

作者： Daved P. Miller Department of Computer Science Virginia Tech Blacksburg VA

ISBN: (纸本)9780911801323

Theoretical work in automated planning research has shown that the popular methods used for doing automated planning either cannot be extended into real world domains, or are computationally intractable. This paper discusses the paradigm of simulation-based planning which attempts to overcome these difficulties. simulation-based planning uses some simulation techniques to gather information for guiding the planner. The resulting system can handle more complex domains with much improved performance over previous systems, while making only a small compromise in completeness. Implemented systems are described.

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A gaussian process based algorithm for stochastic simulation optimization with input distribution uncertainty 20

A gaussian process based algorithm for stochastic simulation...

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Proceedings of the winter simulation conference

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

ISBN: (纸本)9781728194998

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.

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A simulation Analysis of Large Contests with Thresholding Agents

A Simulation Analysis of Large Contests with Thresholding Ag...

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simulation winter conference

作者： Wen Shen Rohan Achar Cristina V. Lopes Department of Informatics University of California Irvine Irvine CA USA

ISBN: (数字)9781728132839

ISBN: (纸本)9781728120522

Running contests has been an effective way to solicit efforts from a large pool of participants. Existing research mostly focuses on small contests that typically consist of two or several perfectly rational agents. In practice, however, agents are often founded in complex environments that involve large numbers of players, and they usually use thresholding policies to make decisions. Despite the fact, there is a surprising lack of understanding of how contest factors influence their outcomes. Here, we present the first simulation analysis on how parameters of the contest success function, the population dynamics, and the agents' cutoff policies influence the outcomes of the contests with thresholding agents that are non-cooperative. Experimental results demonstrate that stakeholders can design (approximately) optimal contests to satisfy both their interests and the agents' by choosing a relatively low bias factor. Our work brings new insights into how to design proper competitions to coordinate thresholding agents.

关键词： Decision making Stakeholders Analytical models Computational modeling Sociology Statistics

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Optimizing complex interaction dynamics in critical infrastructure with a stochastic kinetic model 19

Optimizing complex interaction dynamics in critical infrastr...

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Proceedings of the winter simulation conference

作者： Fan Yang Alina Vereshchaka Wen Dong State University of New York at Buffalo

ISBN: (纸本)9781728132839

Emerging data that track the dynamics of large populations bring new potential for understanding human decision-making in a complex world and supporting better decision-making through the integration of continued partial observations about dynamics. However, existing models have difficulty with capturing the complex, diverse, evolving, and partially unknown dynamics in social networks, and with inferring system state from isolated observations about a tiny fraction of the individuals in the system. To solve real-world problems with a huge number of agents and system states and complicated agent interactions, we propose a stochastic kinetic model that captures complex decision-making and system dynamics using atomic events that are individually simple but together exhibit complex behaviors. As an example, we show how this model offers significantly better results for city-scale multi-objective driver route planning in significantly less time than models based on deep neural networks or co-evolution.

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A Simheuristic Algorithm for the Location Routing Problem with Facility Sizing decisions and Stochastic Demands

A Simheuristic Algorithm for the Location Routing Problem wi...

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simulation winter conference

作者： Rafael D. Tordecilla Javier Panadero Angel A. Juan Carlos L. Quintero-Araújo Jairo R. Montoya-Torres Universitat Oberta de Catalunya Castelldefels SPAIN Faculty of Engineering Universidad de La Sabana Chia COLOMBIA

ISBN: (数字)9781728194998

ISBN: (纸本)9781728195001

Location routing is a well known problem in which decisions about facility location and vehicle routing must be made. Traditionally, a fixed size or capacity is assigned to an open facility as the input parameter to the problem. However, real-world cases show that decision-makers usually have a set of size options. If this size is selected accurately according to the demand of allocated customers, then location decisions and routing activities would raise smaller cost. Nevertheless, choosing this size implies additional variables that make an already NP-hard problem even more challenging. In addition, considering stochastic demands contributes to making the optimization problem more difficult to solve. Hence, a simheuristic algorithm is proposed in this work. It combines the efficiency of metaheuristics and the capabilities of simulation to deal with uncertainty. A series of computational experiments show that our approach can efficiently deal with medium-large instances.

关键词： Uncertainty NP-hard problem Vehicle routing Routing Reliability Optimization Investment

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Distributed simulation in manufacturing: simulation of distributed manufacturing enterprises: a new approach 03

Distributed simulation in manufacturing: simulation of distr...

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Proceedings of the 35th conference on winter simulation: driving innovation

作者： Sameh M. Saad Terrence Perera Ruwan Wickramarachchi Sheffield Hallam University Sheffield U.K.

ISBN: (纸本)9780780381322

The globalization of markets and world-wide competition forces manufacturing enterprises to enter into alliances leading to the creation of distributed manufacturing enterprises. Before forming a partnership it is essential to evaluate viability of proposed enterprise as well as how a company's operations are affected by the proposed virtual enterprise. Distributed simulation provides an attractive tool to make decisions on such situations. However, due to its complexity and high cost distributed simulation failed to gain a wide acceptance from industrial users. This paper presents a new approach for distributed manufacturing simulation (DMS) including a formal methodology for DMS and, implementation approach using current commercial simulation software, employing widely available and cost effective technologies. The main objective of this work is to promote the use of distributed simulation particularly in distributed manufacturing by making it fast to develop and less complicated for implementation.

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General methodology 1: a robust simulation-based multicriteria optimization methodology 02

General methodology 1: a robust simulation-based multicriter...

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Proceedings of the 34th conference on winter simulation: exploring new frontiers

作者： Raid Al-Aomar Jordan University of Science and Technology Irbid Jordan

ISBN: (纸本)9780780376151

This paper describes a methodology for solving Parameter Design (PD) problems in production and business systems of considerable complexity. The solution is aimed at determining optimum settings to system critical parameters so that each system response is at its optimum performance level with least amount of variability. When approaching such problem, analysts are often faced with four major challenges: representing the complex parameter design problem, utilizing an effective search method that is able to explore the problem's complex and large domain, making optimization decisions based on multiple and, often, conflicting objectives, and handling the stochastic variability of in system response as an integral part of the search method. to tackle such challenges, this paper proposes a solution methodology that integrates four state-of-the-art modules of proven methods: simulation Modeling (SM), Genetic Algorithm (GA), Entropy Method (EM), and Robustness Module (RM).

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A Framework for Digital Twin Collaboration

A Framework for Digital Twin Collaboration

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simulation winter conference

作者： Zhengchang Hua Karim Djemame Nikos Tziritas Georgios Theodoropoulos Dept. of Computer Science and Eng. Southern University of Science and Technology (SUSTech) Shenzhen China School of Computing University of Leeds Leeds UK Dept. of Informatics and Telecommunications University of Thessaly Lamia GREECE Research Institute of Trustworthy Autonomous Systems (RITAS) SUSTech Shenzhen China

ISBN: (数字)9798331534202

ISBN: (纸本)9798331534219

Digital Twins (DTs) have emerged as a powerful tool for modeling Large complex Systems (LCSs). Their strength lies in the detailed virtual models that enable accurate predictions, presenting challenges in traditionally centralized approaches due to the immense scale and decentralized ownership of LCSs. This paper proposes a framework that leverages the prevalence of individual DTs within LCSs. By facilitating the exchange of decisions and predictions, this framework fosters collaboration among autonomous DTs, enhancing performance. Additionally, a trust-based mechanism is introduced to improve system robustness against poor decision-making within the collaborative network. The framework's effectiveness is demonstrated in a virtual power plant (VPP) scenario. The evaluation results confirm the system's objectives across various test cases and show scalability for large deployments.

关键词： Accuracy Federated learning Scalability Decision making Collaboration Virtual power plants Predictive models Robustness Digital twins complex systems

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GERMS: an epidemiologic simulation tool for studying geographic and social effects on infection transmission

GERMS: an epidemiologic simulation tool for studying geograp...

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simulation winter conference

作者： A.L. Adams J.S. Koopman S.E. Chick P.J. Yu Department of Epidemiology SPH-1 University of Michigan Ann Arbor MI USA Department of Industrial and Operations Engineering University of Michigan Ann Arbor MI USA

The analysis, surveillance and control of infectious diseases are important functions of public health organizations around the world. This article describes the design and implementation of a simulation toolkit called GERMS (Geographic-Environmental Reinfection Modeling Simulator) that includes several innovations for modeling infectious disease transmission. These tools address several important issues for understanding the epidemiology of sexually transmitted infections. The model accounts for realistic infection transmission systems by explicitly modeling (i) heterogeneous populations of individuals with varying social and geographic characteristics, (ii) complex interactions between individuals to characterize opportunities for transmission, (iii) infection characteristics, such as transmission probabilities and infection duration, and (iv) contact and infection histories. Since public health organizations collect and use information regarding infected individuals, including geographic location and partnership data, the tool is well-equipped to help evaluate the effectiveness of interventions based on that data. We outline design decisions and present the results of initial simulation analysis. We also discuss short-term goals for extending the simulation toolkit to address the specific needs of the Centers for Disease Control.

关键词： Pathogens Diseases Medical simulation Public healthcare Analytical models Surveillance Technological innovation History Computational modeling Observatories

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