Workshop on Simulation Optimization

本次研讨会的研究目标是进一步方法的进步，在模拟优化的设置，其中要优化的目标函数的评估是计算昂贵的。模拟优化中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，来自随机模型或来自离散化非线性动力学）。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两者之间分配，即，在探索搜索空间和获得更好的性能估计之间存在基本的折衷（目标函数）在当前候选解决方案中。模拟在整个美国行业中使用，经常被认为是最广泛使用的运营研究技术，因此如果成功，该研讨会将导致模拟优化方法和技术的进步，为那些可以将其整合到长期战略和战术规划中，以及更直接的执行和日常运营中。应用范围非常广泛，从提高制造业运营、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、定价和对冲的创新。

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.