9713682 Jaillet This research investigates key aspects of real-time dynamic problems in logistics and transportation. The goals of the research are to (1) systematically analyze and integrate the most promising paradigms/solution strategies for dealing with real-time vehicle routing and scheduling problems, (2) formulate adequate corresponding generic models, and (3) develop, analyze, and implement algorithms for solving them. The focus of the research is on the rigorous mathematical analysis of canonical models which would capture the essence of this new class of problems. A main theme of the methodology will be on the integration of a priori optimization, on-line strategy, distributed local heuristics, randomization, and Markov decision process. Interest in the development of real-time and dynamic models of fleet operations and of fleet management systems which are responsive to change in demand, traffic network and other conditions is emerging in many industries and for a wide variety of applications. Managing and making use of the vast quantities of real-time information made available by navigation technologies, satellite positioning systems, automatic vehicle identification systems and spatial GIS databases requires the development of new models and algorithms. This research holds the potential for significant advances in both the theory and applications of such models and algorithms.
