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、呼叫中心人员配置、库存管理、供应链设计、电信网络设计和航空公司调度。对于这些和其他现实问题来说，典型的情况是不能使用已知的概率分布函数来捕捉过程的随机性质，或者如果这是可能的，则所产生的性能测量没有封闭形式的表达式。这些问题的特点是在战略设计阶段必须考虑的随机成分，通常使用随机规划和排队理论来处理。我们探索了另一种对随机分量的分布类型和设置施加较少限制的场所，这导致了数学规划，其中目标函数或约束中的一些项没有闭合形式的表达式，并且必须使用模拟子例程来评估。

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.