Structured Simulation Optimization and Analysis

大量的应用涉及仿真优化，即，通过蒙特卡罗模拟计算的函数的优化。研究的主要目标是开发结构化仿真优化问题的求解方法。“结构化”一词表明问题具有某些结构属性，这些属性可以被优化算法利用，例如，减少求解时间或提高收敛的可能性。更详细地说，本研究的主要目标如下。首先，进一步开发结构化问题的仿真优化方法，其中结构可以用最少的用户输入来检测和验证。第二，将这些方法应用于一系列实际问题，重点是农村地区的紧急服务。第三，创建一个仿真优化问题库，可以用来帮助比较建议的优化方法，并帮助指导新的仿真优化算法的开发。结构化仿真优化方法的开发将允许解决比今天可能解决的更大的模型和相关的优化问题。潜在的应用列表是巨大的，因为蒙特卡罗模拟现在被用于一个巨大的领域，包括但不限于，应急服务规划，制造业，通信系统，服务系统设计和医疗保健。该研究明确包括农村地区应急服务规划的应用，目标是获得更有效的响应时间和覆盖面。其他潜在的好处包括改进的方法，用于网络的操作策略设计，如在电力系统，通信系统和制造业中出现的。应用也存在于医疗保健中，例如癌症患者的外部射束放射治疗计划。

A huge number of applications involve simulation optimization, i.e., the optimization of a function that is computed via Monte Carlo simulation. The primary goal of the research is to develop solution methods for structured simulation optimization problems. The word "structured" suggests that the problem possesses certain structural properties that can be leveraged by optimization algorithms to, for example, reduce solution time or improve the likelihood of convergence. In more detail, the primary goals of this research are as follows. First, to further develop simulation optimization methods for structured problems, where the structure may be detected and verified with minimal user input. Second, to apply those methods on a range of practical problems, with emphasis on emergency services in rural areas. Third, to create a library of simulation optimization problems that can be used to help compare proposed optimization methods, and help guide the development of new simulation-optimization algorithms.The development of structured simulation-optimization methods will allow far larger models and associated optimization problems to be solved than is possible today. The potential list of applications is enormous, since Monte Carlo simulation is now used in a tremendous range of fields including, but certainly not limited to, emergency service planning, manufacturing, communications systems, service system design and health care. The research explicitly includes applications to emergency service planning in rural areas, with the goal of obtaining more effective response times and coverage. Other potential benefits include improved methods for operating policy design for networks such as arise in power systems, communication systems and manufacturing. Applications also exist in health care, such as in external beam radiation treatment planning for cancer patients.