An Optimal Schedule for Urban Road Network Repair Based on the Greedy Algorithm.

Guangquan Lu,Chuan Ding,Ying Xiong,Yunpeng Wang,Zhong-Ke Gao

doi:10.1371/journal.pone.0164780

Abstract

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.

Highlights

Research related to the road network reconstruction plan for earthquakes, floods, and other catastrophic events has noticeably increased over the past decade
We propose the optimal schedule for an urban road network repair based on the greedy algorithm because of its advantages
We propose the optimal schedule for urban road network repair based on the greedy algorithm on the well-known Sioux Falls network (Fig 3), which contains 24 nodes, 76 links, and 576 origin–destination (OD) movements

Summary

Introduction

Research related to the road network reconstruction plan for earthquakes, floods, and other catastrophic events has noticeably increased over the past decade. These events are undeniably important, small daily life events should not be ignored. A wide variety of traffic accidents, car break down, road maintenance, storm-water ponding, road deterioration, and bad weather will cause partial or total reduction in capacity on a given link of urban road network. Increase in road network travel cost, and even a gridlock can happen if these links are not repaired and their capacity are not restored in time. During a heavy rain in Beijing in July 21, 2012, the capacity of the 95 road sections of the urban network became zero, and PLOS ONE | DOI:10.1371/journal.pone.0164780 October 21, 2016

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