Article ID: | iaor20126357 |
Volume: | 9 |
Issue: | 4 |
Start Page Number: | 459 |
End Page Number: | 481 |
Publication Date: | Nov 2012 |
Journal: | Computational Management Science |
Authors: | Daskin Mark, Homem-de-Mello Tito, Smilowitz Karen, Lee Soonhui, Turner Jonathan |
Keywords: | stochastic processes |
We develop a dynamic fleet scheduling model that demonstrates how a carrier can improve fleet utilization. The fleet scheduling model presented by Lee et al. (2012) minimizes (1) a carrier’s fleet size and (2) the penalty associated with the alternative delivery times selected. The model is static since requests are collected over time and processed together. In this paper we present a stochastic, dynamic version of the fleet reduction model. As demand is revealed throughout an order horizon, decisions are made in stages by sampling anticipated demand to avoid recourse penalties in later stages. Based on computational experiments we find the following: