GOALI: Efficient Simulation Techniques for Comparing Constrained Systems

GOALI：用于比较约束系统的高效仿真技术

• 批准号: 0400260
• 负责人: Seong-Hee Kim
• 金额: --
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-06-15 至 2009-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0400260&HistoricalAwards=false
• 关键词: GOALI; Efficient; Simulation; Techniques; Comparing

This Grant Opportunity for Academic Liaison with Industry (GOALI) project is concerned with the construction of highly efficient and statistically valid procedures for comparing systems in the presence of stochastic constraints on the system behavior, assuming that both the objective and the constraints are implicit in a simulation model with few known properties. The goal is to develop statistically valid comparison procedures for solving such simulation optimization problems, and to improve the computational efficiency of the procedures to the point where they can handle up to several thousand alternatives. This involves the use of better variance estimators, common random numbers, and tighter boundaries for comparing systems. The focus of the project will be on optimization problems with discrete decision variables using fully sequential comparison procedures; this is because decision variables in industrial problems are likely to be discrete (e.g., choosing the optimal number of workers and machines) and because sequential procedures have been shown to be extremely efficient relative to other existing comparison approaches.If successful, the research will enhance the use of simulation not only as an assessment tool but also as an optimization tool. Ideally, this project would lead to the implementation of statistically valid and computationally efficient comparison procedures in simulation software; this would be achieved through close collaboration between researchers at Georgia Tech and software vendors (primarily Imagine That!). The addition of such optimization features to popular simulation software packages would be highly valuable to practitioners with respect to identifying process improvements and improved system designs in the presence of constraints about the system behavior.

这项与行业联络的赠款机会（Goali）项目有关构建高效且统计上有效的程序，以比较在系统行为上存在随机限制的情况下的系统，假设目标和约束在模拟模型中都是隐含的，那么几乎没有已知属性。 目的是制定统计上有效的比较程序，以解决此类仿真优化问题，并提高程序的计算效率，直到他们可以处理多达几千种替代方案。 这涉及使用更好的方差估计器，常见的随机数以及比较系统的更紧密的边界。该项目的重点将是使用完全顺序比较程序的离散决策变量的优化问题；这是因为工业问题中的决策变量可能是离散的（例如，选择最佳的工人和机器数量），并且因为相对于其他现有比较方法，已证明顺序程序非常有效。如果成功，该研究将增强模拟的使用不仅作为评估工具，还可以作为优化工具。 理想情况下，该项目将导致在模拟软件中实施统计有效和有效的比较程序。这将通过佐治亚理工学院和软件供应商的研究人员之间的密切合作（主要是想象！）来实现。 在识别过程改进和改进系统行为的限制下，将这种优化功能添加到流行的仿真软件包中对于从业人员而言，将非常有价值。