Sensitivity Analysis of a Dynamic Fleet Management Model Using Approximate Dynamic Programming
提出了一种无需多次仿真的方法，用于评估随机动态车队管理模型对车队规模和负载可用性的灵敏度，能快速计算增加一辆车或一个负载时目标函数值的变化。
We present tractable algorithms to assess the sensitivity of a stochastic dynamic fleet management model to fleet size and load availability. In particular, we show how to compute the change in the objective function value in response to an additional vehicle or an additional load introduced into the system. The novel aspect of our approach is that it does not require multiple simulations with different values of the model parameters, and in this respect it differs from trial-and-error-based “what-if” analyses. Numerical experiments show that the proposed methods are accurate and computationally attractive.