Abstract
Fleet sizing and empty equipment redistribution are important issues in managing transportation systems. Most of the mathematical models that have been developed for these problems are complex and computationally demanding, including dynamic linear programming and stochastic/dynamic mathematical programs. Our research takes an alternate approach by building from inventory theory and developing decentralized stock control policies for empty equipment. This approach is applied to hub-and-spoke networks (i.e., center-terminal networks), by first analytically modeling the stochastic processes representing various stock-control variables, and then comparing the analytical results to monte-carlo simulations. A decomposition approach is also developed to determine stock-out probabilities as a function of the fleet size as a whole, and as a function of localized control parameters.