由客座编辑Paul F. Evangelista上校和LTC James H. Schreiner撰写的前言

Paul F. Evangelista, James H. Schreiner
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引用次数: 0

摘要

《工业与系统工程评论》的这一期特刊再次展示了在纽约西点美国军事学院举行的唐纳德·r·基思将军纪念顶点会议上的顶级论文。尽管持续的COVID限制,真正创新的会议包括来自学术界和产业界的50多名现场和远程评委的现场演讲,创造了一个高质量的活动,突出了本科生团队的研究。经过对50余篇学术论文的评比,本刊所列的8篇论文入选本刊特刊。讨论的主题广泛而多样,但不确定和复杂环境中的决策支持成为一个主题。工业和系统工程师完成的大部分工作都集中在通过我们的行业工具做出正确的决策上。这些论文中调查的工具套件代表了一些最先进的方法,以及在一个独特的应用领域中经过时间验证的技术。军事应用占据了几篇论文的主导地位。唐尼等人研究了训练中代表军事作战行为的海量数据集,试图更好地理解军事作战能力。Ungrady和Dabkowski通过模糊认知地图的应用来解决美国军队招募的复杂性,寻找因果关系。Middlebrooks等人应用系统动力学建模研究了军事采买系统决策。过程改进代表了另一个子主题,继续关注决策支持。Enos等人将精益六西格玛技术应用于制造过程。Katz等人探索了生物医学机器维护调度,为复杂的调度任务寻求最优解决方案。Kaloudelis等人为大学开发了一个流行病决策支持程序。第三个子主题是应用于信息领域的分析和机器学习技术。克鲁格和埃诺斯开发了分析方法来支持冰球战略。Manzonelli等人将自然语言处理应用于信息操作,试图自动检查数量惊人的叙述性数据,这些数据试图塑造信念和态度。请和我一起祝贺我们的作者,特别是为本期内容的撰写提供了主要智力努力的年轻本科学者们。James H. Schreiner,博士,PMP, CPEM, F. asem LTC(P),美国陆军副教授,USMA学院教授,工程管理(EM)项目部主任,陆军垒球美国军事学院马汉大厅420室,纽约西点,邮编:james.schreiner@westpoint.edu
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Foreword by Guest Editors COL Paul F. Evangelista & LTC James H. Schreiner
This special issue of the Industrial and Systems Engineering Review once again showcases the top papers from the annual General Donald R. Keith memorial capstone conference at the United States Military Academy in West Point, NY. Despite continued COVID restrictions, the truly innovative conference included a mix of in-person presentations with over 50 live and remote judges from across academia and industry to create a high-quality event highlighting the undergraduate student team research. After consideration of over 50 academic papers, the eight listed in this issue were selected for publication in this special issue of the journal. The topics discussed are broad and diverse, however decision support within an uncertain and complex environment emerges as a theme. Much of the work completed by industrial and systems engineers focuses on getting decisions right by means of the tools of our trade. The suite of tools surveyed within these papers represents several state-of-the-art methods as well as time-proven techniques within a unique application domain. Military applications dominated several of the papers. Downey et al. studied massive datasets that represent military operational behaviors in training, seeking to better understand military operational capabilities. Ungrady and Dabkowski tackled the complexities of US Army recruiting through the application of fuzzy cognitive maps, searching for causation. Middlebrooks et al. studied military acquisition system decisions, applying system dynamics modeling. Process improvement represented another sub-theme, with continued focus on decision support. Enos et al. applied lean six sigma techniques to manufacturing processes. Katz et al. explored biomedical machine maintenance scheduling, seeking optimal solutions to a complex scheduling task. Kaloudelis et al. developed a pandemic decision support process for universities. Analytics and machine learning techniques applied to the information domain dominated the third sub-theme. Krueger and Enos developed analytics to support ice hockey strategies. Manzonelli et al. applied natural language processing against information operations, seeking to automate the examination of incredible amounts of narrative data that seek to shape beliefs and attitudes. Please join me in congratulating our authors, especially the young undergraduate scholars that provided the primary intellectual efforts that created the contents of this issue. COL Paul F. Evangelista Chief Data Officer United States Military Academy Taylor Hall, 5th Floor West Point, NY 10996 Email: paul.evangelista@westpoint.edu James H. Schreiner, PhD, PMP, CPEM, F.ASEM LTC(P), U.S. Army Associate Professor USMA Academy Professor Director, Engineering Management (EM) Program Department of Systems Engineering Head Officer Representative, Army Softball United States Military Academy Room 420 Mahan Hall West Point, NY 10996 Email: james.schreiner@westpoint.edu
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