Short-Term Scheduling of Vehicle Testing System Using Object Petri Net

This paper addresses the modeling, analysis, and scheduling optimization of a vehicle testing system, a widely used facility in China's transportation management and automotive manufactures. To do so, object Petri net models are built to describe its resources (including testing equipment and field) and operations. Based on these models, a short-term scheduling framework and an algorithm for optimally generating a vehicle's testing sequence are presented. By this framework, a waiting area with adjustable capacity is set for vehicles to be inspected in the system. The complete permutations of vehicles in the waiting area are considered as tokens in an object Petri net. In this way, with the models, the total testing turnaround time of a vehicle sequence can be calculated and the optimal one can be chosen. Experimental results show that the proposed method can reduce the average testing turnaround time by about 31% compared with the traditional first-come-first-served-based one. In addition, the proposed method can obtain a shorter average testing turnaround time when the re-inspection rates are 25%, 50%, 75%, and 100%. Thus, it is applicable and effective.