Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching

Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching

A important, but seldom investigated, issue in the field of dynamic vehicle routing and dispatching is how to exploit information about future events to improve decision making. In this paper, we address this issue in a real-time setting with a strategy based on probabilistic knowledge about future request arrivals to better manage the fleet of vehicles. More precisely, the new strategy introdu...

Diversion Issues in Real-Time Vehicle Dispatching

Recent technological advances in communication systems now allow the exploitation of realtime information for dynamic vehicle routing and scheduling. It is possible, in particular, to consider diverting a vehicle away from its current destination in response to a new customer request. In this paper, a strategy for assigning customer requests, which includes diversion, is proposed, and various i...

Parallel Tabu Search for Real-Time Vehicle Routing and Dispatching

A real-time recursive dynamic model for vehicle driving simulators

This paper presents the Real-Time Recursive Dynamics (RTRD) model that is developed for driving simulators. The model could be implemented in the Driving Simulator. The RTRD can also be used for off-line high-speed dynamics analysis, compared with commercial multibody dynamics codes, to speed up mechanical design process. An overview of RTRD is presented in the paper. Basic models for specific ...

Competitive Vehicle Routing Problem with Time Windows and Stochastic Demands

The competitive vehicle routing problem is one of the important issues in transportation area. In this paper a new method for competitive VRP with time windows and stochastic demand is introduced. In the presented method a three time bounds are given and the probability of arrival time between each time bound is assumed to be uniform. The demands of each customer are different in each time wind...