Workshop on Simulation Optimization

本次研讨会的研究目标是进一步在模拟优化的方法上取得进展，其中要优化的目标函数的评估在计算上是昂贵的。仿真优化的主要复杂因素是目标函数的非线性（和非凸性）和高维性（例如，来自随机模型或离散非线性动力学）。使模拟优化比普通优化更困难的另一个关键特征是，计算负担必须在搜索和评估之间分配，也就是说，在探索搜索空间和在当前候选解决方案上获得更好的性能估计（目标函数）之间存在基本的权衡。模拟在整个美国工业中使用，经常被引用为最广泛使用的运筹学技术，因此，如果成功，本次研讨会将导致模拟优化方法和技术的进步，这将为那些能够将其整合到长期战略和战术规划中的公司提供竞争优势，以及在他们更直接的执行和日常运营中。从提高制造业务、供应链管理、电信和运输网络/系统（航空、铁路、公路）的效率，到金融工程产品、定价和对冲方面的创新，应用范围非常广泛。

The research objective of this workshop is to further methodological advances in simulation optimization for the setting in which evaluation of the objective function to be optimized is computationally expensive. The major complicating factors in simulation optimization are nonlinearities (and non-convexity) in the objective function and high dimensionality (e.g., from stochastic models or from discretizing nonlinear dynamics). A further key feature that makes simulation optimization more difficult than ordinary optimization is that the computational burden must be allocated between both the search and the evaluation, i.e., there is a basic tradeoff between exploring the search space and obtaining a better estimate of the performance (objective function) at the current candidate solutions.Simulation is used throughout the US industry, frequently cited as the most widely used operations research technique, so if successful, this workshop will lead to advances in simulation optimization methodologies and techniques that would provide a competitive advantage to those companies that can integrate them in their long-term strategic and tactical planning, as well as in their more immediate execution and daily operations. Applications are numerous, from improved efficiencies in manufacturing operations, supply chain management, and telecommunications and transportation networks/systems (air, rail, road) to innovations in financial engineering products, pricing, and hedging.