Workshop: Simulation for Better Decisions in an Uncertain World, July 5-7, 2007 at INSEAD in Fontainebleau, France

研讨会：在不确定的世界中进行更好决策的模拟，2007 年 7 月 5 日至 7 日，法国枫丹白露欧洲工商管理学院 (INSEAD)

• 批准号: 0703665
• 负责人: Shane Henderson
• 金额: $ 2.36万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-05-01 至 2007-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0703665&HistoricalAwards=false
• 关键词: Workshop; Simulation; Better; Decisions; Uncertain

The first INFORMS Simulation Society Research Workshop will be held July 5-7, 2007 at the Fontainebleau, France campus of INSEAD. The theme is Simulation for better decisions in an uncertain world". The goal of the workshop is to bring together leading researchers working in a variety of theoretical, empirical, application and implementation domains in order to reflect on a central question: how can simulation most effectively support better decisions? More specifically, the topics include the following. What are the strengths and limitations of existing simulation optimization techniques for both continuous and discrete optimization? Can we exploit links with closely related disciplines, such as stochastic programming and robust optimization? What role do sensitivity analysis, uncertainty analysis, the robustness of decisions to modelling assumptions, implementation issues, and special considerations that arise in specific applications have to play in the choice of algorithm and performance thereof? What demands are placed on existing simulation tools that are used in a variety of applications? Where are the gaps in existing simulation optimization theory? Extended abstracts will be made available openly on the WWW and the conference organizers will serve as guest editors in a special issue of the ACM Transactions on Modeling and Computer Simulation that will feature selected articles from the workshop.

首届INFORMS仿真学会研究研讨会将于2007年7月5日至7日在INSEAD法国枫丹白露校区举行。主题是“模拟在不确定的世界中做出更好的决策”。研讨会的目标是将在各种理论、经验、应用和实施领域工作的领先研究人员聚集在一起，以反思一个核心问题：如何最有效地支持更好的决策？更具体地说，主题包括以下内容。现有的模拟优化技术在连续和离散优化方面的优势和局限性是什么？我们能否利用与密切相关的学科之间的联系，比如随机规划和鲁棒优化？敏感性分析、不确定性分析、决策对建模假设的鲁棒性、实施问题以及特定应用中出现的特殊考虑因素在算法的选择及其性能中起什么作用？对各种应用中使用的现有仿真工具提出了什么要求？现有仿真优化理论的差距在哪里？扩展摘要将在WWW上公开提供，会议组织者将担任《ACM建模与计算机仿真学报》特刊的客座编辑，该特刊将精选研讨会中的文章。