9309579 Papastavrou Real-world vehicle routing problems are characterized by imprecise or unknown information about future customers and travel times, constantly changing planning horizons, queuing considerations, resequencing and reassignment decisions, and a variety of performance criteria that include waiting time and delivery costs. However, classical vehicle routing models are static, assume perfect knowledge of demands, ignore queuing effects and typically only consider travel costs. Only recently, have new approaches been investigated, taking into consideration both the dynamic and the stochastic aspects of the problems. The researchers will combine techniques from both areas of operations research, stochastics and combinatorics, to analyze a variety of stochastic and dynamic (mainly vehicle routing) problems; these problems are more applicable than their traditional deterministic counterparts. Research results will demonstrate that the models will not only be useful for transportation planning, but also for other classes of problems where congestion effects dominate; these include scheduling problems, bin-packing problems, facility location problems, and a special class of information retrieval problems in computer science.
