Simulation-based optimization for strategic design problems

我们探索了一种新的方法来解决各种现实生活中的战略设计问题，包括物流规划，呼叫中心人员配备，库存管理，供应链设计，电信网络设计和航空公司调度。这是典型的，对于这些和其他现实的问题，该过程的随机性质不能被捕获使用一个已知的概率分布函数，或者如果这是可能的，所得到的性能指标没有一个封闭的形式表示。这些问题的特点是一个随机组件，必须考虑到在战略设计阶段，通常采用随机规划和排队论。我们探索另一个场地，施加较少的限制的类型的分布和设置的随机组件，导致数学程序中的一些条款的目标函数或约束条件没有一个封闭的形式的表达，必须使用模拟子程序进行评估。

We explore a novel approach to solve a variety of real-life strategic design problems that include logistics planning, call center staffing, inventory management, supply chain design, telecommunication network design, and airline scheduling. It is typical for these, and other realistic problems, that the stochastic nature of the process can not be captured using a known probability distribution function, or if this is possible the resulting performance measures do not have a closed form expression. These problems are characterized by a stochastic component that has to be taken into account at the strategic design stage, and are typically approached using stochastic programming and queuing theory. We explore another venue that imposes less restrictions on the type of distribution and setting of the stochastic component, leading to mathematical programs where some of the terms in the objective function or the constraints do not have a closed form expression and have to be evaluated using a simulation subroutine.