Dynamic Truckload Truck Routing and Scheduling in Oversaturated Demand Situations

Abstract

The problem considered is dynamic online truckload routing and scheduling with time windows operating in oversaturated conditions, that is, when the demand for service exceeds the system’s average capacity. The relationship between computation time and the solution quality, measured by system efficiency and response time, is discussed. A dynamic operation process for implementing various algorithms and procedures is described, with the aim of fully utilizing computational resources without wasting available time between successive demand requests. In addition, particularly when demand arrival rates result in oversaturated system conditions, application of intelligent acceptance and filtering decision procedures that consider system status and demand characteristics can result in significant operational benefits. Simulation experiments conducted to evaluate the relative performance of the proposed approaches confirm the existence of significant improvement potential in terms of both system efficiency and response time over previous approaches.

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