Proceedings of the Winter Simulation Conference 2014

7-10 Dec. 2014

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Displaying Results 1 - 25 of 356
  • [Front matter]

    Publication Year: 2014, Page(s):1 - 4
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    Freely Available from IEEE
  • Table of contents

    Publication Year: 2014, Page(s):1 - 41
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    Freely Available from IEEE
  • The Higgs Boson - the search for the particle and the role of simulation

    Publication Year: 2014, Page(s):1 - 2
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (66 KB)

    Answers to pressing questions in high-energy physics may lie in electroweak symmetry breaking, the phenomenon for explaining why the weak and electromagnetic forces are different. From solving the mystery of dark energy to string theory, our entire philosophy depends on the unknown physics at the electroweak scale. The hunt for the elusive Higgs boson has gone on for almost half a century. Its dis... View full abstract»

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  • John Swanson and ANSYS - An engineering success story

    Publication Year: 2014, Page(s):3 - 4
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    This talk will begin with an overview of the life of John Swanson, showing that his success was due to a community effort, and celebrating the people and institutions which made his engineering contributions possible. A milestone in this path is the awarding of the John Fritz Medal, said to be the highest award in the engineering profession. The rest of this talk will be a non-technical history of... View full abstract»

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  • Parallel and distributed simulation

    Publication Year: 2014, Page(s): 5
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    Driven by the widespread availability of commercial multiprocessor systems and advances in computer networking, the parallel and distributed simulation field emerged and flourished in the late 1970s and 1980s. The field has evolved since that time to address critical issues such as synchronization and interoperability, and remains an active area of research to this day. Many impressive successes h... View full abstract»

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  • Introductory tutorial: Agent-based modeling and simulation

    Publication Year: 2014, Page(s):6 - 20
    Cited by:  Papers (34)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (352 KB) | HTML iconHTML

    Agent-based simulation (ABS) is an approach to modeling systems comprised of individual, autonomous, interacting “agents.” Agent-based modeling offers ways to more easily model individual behaviors and how behaviors affect others in ways that have not been available before. There is much interest in developing agent-based models for many application problem domains. Applications range from modelin... View full abstract»

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  • Simulation optimization: A tutorial overview and recent developments in gradient-based methods

    Publication Year: 2014, Page(s):21 - 35
    Cited by:  Papers (16)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (217 KB) | HTML iconHTML

    We provide a tutorial overview of simulation optimization methods, including statistical ranking & selection (R&S) methods such as indifference-zone procedures, optimal computing budget allocation (OCBA), and Bayesian value of information (VIP) approaches; random search methods; sample average approximation (SAA); response surface methodology (RSM); and stochastic approximation (SA... View full abstract»

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  • Introduction to supply chain simulation

    Publication Year: 2014, Page(s):36 - 50
    Cited by:  Papers (1)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (1344 KB) | HTML iconHTML

    Although a corporation does not own all of its supply chain, the entire chain is responsible for product delivery and customer satisfaction. As one of several methodologies available for supply chain analysis, simulation has distinct advantages and disadvantages when compared to other analysis methodologies. This tutorial will detail the reasons why one would want to use simulation as the analysis... View full abstract»

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  • Computational probability applications

    Publication Year: 2014, Page(s):51 - 65
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (215 KB) | HTML iconHTML

    There is a boundary separating analytic methodology and simulation methodology. If a problem involves the flipping of coins or the rolling of dice, for example, analytic methods are generally employed. If a problem involves a complex series of queues with a nonstationary arrival stream, discrete-event simulation methods are generally employed. This tutorial considers problems that are near the bou... View full abstract»

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  • A tutorial on design of experiments for simulation modeling

    Publication Year: 2014, Page(s):66 - 80
    Cited by:  Papers (9)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (300 KB) | HTML iconHTML

    Simulation models often have many input factors, and determining which ones have a significant impact on performance measures (responses) of interest can be a difficult task. The common approach of changing one factor at a time is statistically inefficient and, more importantly, is very often just incorrect, because for many models factors interact to impact on the responses. In this tutorial we p... View full abstract»

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  • Simulation attacks manufacturing challenges

    Publication Year: 2014, Page(s):81 - 89
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (177 KB) | HTML iconHTML

    All during the past half-century, the environment of computing applications has evolved from large, comparatively slow mainframes with storage small and expensive by today's standards to desktops, laptops, cloud computing, fast computation, graphical capabilities, and capacious flash drives carried in pocket or purse. All this time, discrete-event process simulation has steadily grown in power, ea... View full abstract»

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  • Tutorial: Tips for successful practice of simulation

    Publication Year: 2014, Page(s):90 - 97
    Cited by:  Papers (4)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (261 KB) | HTML iconHTML

    A simulation project is much more than building a model and the skills required for success go well beyond knowing a particular simulation tool. A 30 year veteran discusses some important steps to enable project success and some cautions and tips to help avoid common traps. This content is similar to presentations given at previous WSC conferences. View full abstract»

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  • A practical look at simulation project management

    Publication Year: 2014, Page(s):98 - 102
    Cited by:  Papers (3)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (145 KB) | HTML iconHTML

    While the management of a simulation project has many of the characteristics of traditional project management, it also has a number of unique issues that must be addressed. This paper will address the common, the not-so-common, and the treacherous aspects of simulation project management. A simulation specific series of steps will be presented. The paper also includes examples of past projects, t... View full abstract»

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  • Tutorial: Information and Process Modeling for simulation

    Publication Year: 2014, Page(s):103 - 117
    Cited by:  Papers (5)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (493 KB) | HTML iconHTML

    Like a system model in Information Systems and Software Engineering (IS/SE), a system model in simulation engineering mainly consists of an information model and a process model. In the fields of IS/SE there are widely used standards such as the Class Diagrams of the Unified Modeling Language (UML) for making information models, and the Business Process Modeling Notation (BPMN) for making process ... View full abstract»

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  • Verifying and validating simulation models

    Publication Year: 2014, Page(s):118 - 131
    Cited by:  Papers (6)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (433 KB) | HTML iconHTML

    In this paper verification and validation of simulation models are discussed. Different approaches to deciding model validity are described and a graphical paradigm that relates verification and validation to the model development process is presented and explained. Conceptual model validity, model verification, operational validity, and data validity are discussed and a recommended procedure for ... View full abstract»

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  • Inside discrete-event simulation software: How it works and why it matters

    Publication Year: 2014, Page(s):132 - 146
    Cited by:  Papers (3)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (328 KB) | HTML iconHTML

    This paper provides simulation practitioners and consumers with a grounding in how discrete-event simulation software works. Topics include discrete-event systems; entities, resources, control elements and operations; simulation runs; entity states; entity lists; and their management. The implementations of these generic ideas in AutoMod, SLX, ExtendSim, and Simio are described. The paper conclude... View full abstract»

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  • How to develop your own simulators for discrete-event systems

    Publication Year: 2014, Page(s):147 - 161
    Cited by:  Papers (1)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (4119 KB) | HTML iconHTML

    This tutorial explains how to develop dedicated simulators for executing event graph models and activity cycle diagram (ACD) models. An event-graph simulator template and an ACD simulator template are presented in pseudo code form, together with example C# implementations for a simple discrete-event system. A list of the simulation programs in C# codes is provided in a website. A brief description... View full abstract»

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  • Advanced tutorial: Input uncertainty quantification

    Publication Year: 2014, Page(s):162 - 176
    Cited by:  Papers (21)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (150 KB) | HTML iconHTML

    “Input uncertainty” refers to the (often unmeasured) effect of not knowing the true, correct distributions of the basic stochastic processes that drive the simulation. These include, for instance, interarrival-time and service-time distributions in queueing models; bed-occupancy distributions in health care models; distributions for the values of underlying assets in financial models; and time-to-... View full abstract»

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  • Multi-level modeling and simulation of cell biological systems with ML-Rules - A tutorial

    Publication Year: 2014, Page(s):177 - 191
    Cited by:  Papers (2)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (170 KB) | HTML iconHTML

    Multi-level modeling is concerned with describing a system at different levels of organization and relating their dynamics. ML-Rules is a rule-based language developed for supporting the modeling of cell biological systems. It supports nested rule schemata, the hierarchical dynamic nesting of species, the assignment of attributes and solutions to species at each level, and a flexible definition of... View full abstract»

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  • A tutorial on Cloud computing for Agent-based Modeling & Simulation with Repast

    Publication Year: 2014, Page(s):192 - 206
    Cited by:  Papers (9)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (7773 KB) | HTML iconHTML

    Cloud computing facilitates access to elastic high performance computing without the associated high cost. Agent-based Modeling & Simulation (ABMS) is being used across many scientific disciplines to study complex adaptive systems. Repast Simphony (Recursive Porous Agent Simulation Toolkit) is a widely used ABMS system. Cloud computing can speed-up significantly ABMS to facilitate more accurat... View full abstract»

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  • Understanding complex systems: Using interaction as a measure of emergence

    Publication Year: 2014, Page(s):207 - 218
    Cited by:  Papers (7)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (348 KB) | HTML iconHTML

    Understanding the behavior of complex systems is becoming a crucial issue as systems grow in size, and the interconnection and geographical distribution of their components diversifies. The interaction over time of many components often leads to emergent behavior, which can be harmful to the system. Despite this, very few practical approaches for the identification of emergent behavior exist, and ... View full abstract»

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  • Multifractal time series analysis of positive-intelligence agent-based simulations of financial markets

    Publication Year: 2014, Page(s):219 - 230
    Cited by:  Papers (1)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (1347 KB) | HTML iconHTML

    To analyze the impact of intelligent traders with differing fundamental motivations on agent-based simulations of financial markets, we extend the classical zero-intelligence model of financial markets to a positive-intelligence model using the MASON agent-based modeling framework. We exploit multifractal detrended fluctuation analysis (MF-DFA) to analyze the series of stock prices generated by th... View full abstract»

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  • A novel multi-agent system for complex scheduling problems

    Publication Year: 2014, Page(s):231 - 241
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (421 KB) | HTML iconHTML

    Complex scheduling problems require a large amount computation power and innovative solution methods. The objective of this paper is the conception and implementation of a multi-agent system that is applicable in various problem domains. Independent specialized agents handle small tasks, to reach a superordinate target. Effective coordination is therefore required to achieve productive cooperation... View full abstract»

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  • Investigating the hidden losses caused by out-of-shelf events: A multi-agent-based simulation

    Publication Year: 2014, Page(s):242 - 251
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (510 KB) | HTML iconHTML

    Out-of-shelf events refer to periods of time in which items of a certain product are not available to customers. It is clear that incidents of this nature result in economic loss, but their side effects are much more profound: since there is no record of missed sales opportunities, the estimated demand curve tends to be inaccurate. As a result, order placement strategies employed by retailers are ... View full abstract»

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  • Modeling population displacement in the Syrian city of Aleppo

    Publication Year: 2014, Page(s):252 - 263
    Cited by:  Papers (5)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (823 KB) | HTML iconHTML

    The persistent crisis in Syria has affected millions of its citizens by forcing their displacement from native or accustomed residences. Modeling the Syrian conflict provides a computational means to better understand why, when, and where these citizens flee. Thus, an agent-based model drawn on real-world data to represent Syrian cities (the environment) and the demographic constitution of those c... View full abstract»

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