Topics in real-time fleet management

Abstract

This is a summary of the author’s Ph.D. thesis, supervised by Gianpaolo Ghiani and Barrett W. Thomas and defended on 21 February 2008, at the Università degli Studi della Calabria. The thesis is written in English and is available from the author upon request. In this work, various tactical and operational issues concerning real-time fleet management are studied. First, we introduce the Dynamic and Stochastic Traveling Salesman Problem and propose an optimal policy through a Markov Decision Process as well as develop lower and upper bounds on the optimal policy cost. Then, we present several strategies for implementing a priori routes, and we identify situations in which the use of more involved a priori strategies can give some benefit. Next, we consider the Dynamic and Stochastic Vehicle Dispatching Problem with Pickups and Deliveries, for which we develop anticipatory algorithms that evaluate alternative solutions through a short-term demand sampling and a fully sequential procedure for indifference zone selection. Finally, we propose Approximated Neighborhood Evaluation procedures for the same-day Courier Shift Scheduling Problem, a tactical problem which amounts to minimizing the staffing cost subject to probabilistic service level requirements.