The schedule of urban road network recovery caused by rainstorms, snow, and other bad weather conditions, traffic incidents, and other daily events is essential. However, limited studies have been conducted to investigate this problem. We fill this research gap by proposing an optimal schedule for urban road network repair with limited repair resources based on the greedy algorithm. Critical links will be given priority in repair according to the basic concept of the greedy algorithm. In this study, the link whose restoration produces the ratio of the system-wide travel time of the current network to the worst network is the minimum. We define such a link as the critical link for the current network. We will re-evaluate the importance of damaged links after each repair process is completed. That is, the critical link ranking will be changed along with the repair process because of the interaction among links. We repair the most critical link for the specific network state based on the greedy algorithm to obtain the optimal schedule. The algorithm can still quickly obtain an optimal schedule even if the scale of the road network is large because the greedy algorithm can reduce computational complexity. We prove that the problem can obtain the optimal solution using the greedy algorithm in theory. The algorithm is also demonstrated in the Sioux Falls network. The problem discussed in this paper is highly significant in dealing with urban road network restoration.

No abstract

Worst-case end-to-end delay analysis is important for real-time applications of switched Ethernet network. The Trajectory approach is one of the mature tools for worst-case delay analysis to calculate the upper bound of delay. The delay analysis based on the Trajectory approach as well as the packet serialisation of such networks is presented. An optimisation of packet serialisation is proposed in order to improve the Trajectory approach. A case study is illustrated to compare the improved Trajectory approach with the classical one, and the result shows that the improved Trajectory approach can get tighter upper bound of end-to-end delay.

No abstract