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2013 Winter Simulations Conference (WSC)

8-11 Dec. 2013

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Displaying Results 1 - 25 of 365
  • Call for papers & presentations

    Publication Year: 2013, Page(s): 1
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  • Author index

    Publication Year: 2013, Page(s):1 - 65
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  • Board of directors

    Publication Year: 2013, Page(s):1 - 2
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  • Conference committee

    Publication Year: 2013, Page(s): 1
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  • Track coordinators

    Publication Year: 2013, Page(s):1 - 3
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  • Author directory

    Publication Year: 2013, Page(s):1 - 149
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  • The WSC foundation

    Publication Year: 2013, Page(s):1 - 3
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  • Future Winter Simulation conferences

    Publication Year: 2013, Page(s): 1
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  • [Title page]

    Publication Year: 2013, Page(s): 1
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  • Keynote address

    Publication Year: 2013, Page(s):1 - 4
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2654 KB)

    Provides an abstract for each of the keynote presentations and a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings. View full abstract»

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  • Preface

    Publication Year: 2013, Page(s):1 - 4
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  • Program committee members & referees

    Publication Year: 2013, Page(s):1 - 6
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  • Sponsoring societies

    Publication Year: 2013, Page(s): 1
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  • Table of contents

    Publication Year: 2013, Page(s):1 - 34
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  • Big Data and the bright future of simulation — The case of agent-based modeling

    Publication Year: 2013, Page(s): 1
    Cited by:  Papers (1)
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  • Deliver us from complexity

    Publication Year: 2013, Page(s): 2
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  • Simulation and software through 50 years

    Publication Year: 2013, Page(s): 3
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  • The simulation Curmudgeon

    Publication Year: 2013, Page(s): 4
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  • Managing on-demand computing services with heterogeneous customers

    Publication Year: 2013, Page(s):5 - 16
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (470 KB) | HTML iconHTML

    Cloud computing allows the practice of allocating shared computational resources to a diverse set of customers in an on demand fashion. The heterogeneity of customers' requirements can be characterized by the frequency of demand, the value associated with the service and delay sensitivity. We consider the following two classes of customers: frequent users (FC) and urgent users (UR). The FC agreeme... View full abstract»

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  • Efficient learning of donor retention strategies for the American Red Cross

    Publication Year: 2013, Page(s):17 - 28
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1479 KB) | HTML iconHTML

    We present a new sequential decision model for adaptively allocating a fundraising campaign budget for a non-profit organization such as the American Red Cross. The campaign outcome is related to a set of design features using linear regression. We derive the first simulation allocation procedure for simultaneously learning unknown regression parameters and unknown sampling noise. The large number... View full abstract»

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  • Learning logistic demand curves in business-to-business pricing

    Publication Year: 2013, Page(s):29 - 40
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1353 KB) | HTML iconHTML

    This work proposes an approximate Bayesian statistical model for predicting the win/loss probability for a given price in business-to-business (B2B) pricing. This model allows us to learn parameters in logistic regression based on binary (win/loss) data and can be quickly updated after each new win/loss observation. We also consider an approach for recommending target prices based on the approxima... View full abstract»

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  • Combined DES/SD simulaton model of breast cancer screening for older women: An overview

    Publication Year: 2013, Page(s):41 - 53
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (439 KB) | HTML iconHTML

    We develop a simulation modeling framework for evaluating the effectiveness of breast cancer screening policies for US women of age 65+. We introduce a two-phase simulation approach to modeling the main components in the breast cancer screening process. The first phase is a natural-history model of the incidence and progression of untreated breast cancer in randomly sampled individuals from the de... View full abstract»

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  • Admission control in a pure loss healthcare network: MDP and DES approach

    Publication Year: 2013, Page(s):54 - 65
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (362 KB) | HTML iconHTML

    This paper considers admission control policies in a pure-loss hierarchical perinatal network where there are 2 parallel multi-server (target) hospitals fed by new arriving patients and overflowed patients from a set of parallel multi-server hospitals. In this perinatal network setting, we consider the problem of finding an optimal admission policy that recommends how many beds to reserve in two t... View full abstract»

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  • A modular simulation model for assessing interventions for abdominal aortic aneurysms

    Publication Year: 2013, Page(s):66 - 76
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (360 KB) | HTML iconHTML

    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 scre... View full abstract»

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  • Two-stage likelihood robust linear program with application to water allocation under uncertainty

    Publication Year: 2013, Page(s):77 - 88
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (244 KB) | HTML iconHTML

    We adapt and extend the likelihood robust optimization method recently proposed by Wang, Glynn, and Ye for the newsvendor problem to a more general two-stage setting. We examine the value of collecting additional data and the cost of finding a solution robust to an ambiguous probability distribution. A decomposition-based solution algorithm to solve the resulting model is given. We apply the model... View full abstract»

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