Workshop on Simulation Optimization

本次研讨会的研究目标是在模拟优化方面取得进一步的方法学进展，在这种情况下，对要优化的目标函数的评估在计算上是昂贵的。仿真优化中的主要复杂因素是目标函数中的非线性(和非凸性)和高维(例如，来自随机模型或来自离散化的非线性动力学)。使仿真优化比普通优化更困难的另一个关键特征是，必须在搜索和评估之间分配计算负担，即在探索搜索空间和获得对当前候选解决方案的性能(目标函数)的更好估计之间存在基本权衡。整个美国行业都在使用仿真，经常被认为是最广泛使用的运筹学技术，所以如果成功，这次研讨会将导致仿真优化方法和技术的进步，这些方法和技术将为那些能够将其整合到长期战略和战术规划中，以及在更直接的执行和日常运营中提供竞争优势的公司提供竞争优势。应用领域很多，从提高制造运营、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、定价和套期保值的创新。

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.