Management of Pavement Maintenance, Rehabilitation, and Reconstruction through Network Partition

Author:

Gao Lu1,Zhang Zhanmin2

Affiliation:

1. Department of Construction Management, University of Houston, Houston, TX 77204.

2. Department of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, Austin, TX 78712.

Abstract

This paper presents a new optimization model for addressing the problem of planning pavement maintenance, rehabilitation, and reconstruction (MRR) for a large-scale road network. In the past, this problem has usually been formulated as a linear programming or integer programming model. The solutions obtained from those models determine the timing, location, and type of treatment needed to perform the MRR operation for a given planning horizon. A shortcoming of such models is that the sections selected for MRR are usually distributed spatially across the network, and this distribution makes it difficult to plan and implement MRR activities in a coordinated manner. To take advantage of economies of scale, adjacent road sections with similar MRR needs should be maintained within a single project. However, the idea of automatically combining adjacent sections into one large project has not been given serious attention in existing optimization models for pavement MRR planning. This paper proposes a new approach to pavement MRR planning that utilizes the spatial structure of the road network. The road network is first partitioned into groups of adjacent sections, or MRR projects, with similar MRR needs. Then a knapsack problem is solved to optimally allocate resources to selected MRR projects with the objective of maximizing system performance.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Cited by 19 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3