Bridge network maintenance prioritization under budget constraint

被引:47
|
作者
Zhang, Weili [1 ]
Wang, Naiyu [2 ]
机构
[1] Univ Oklahoma, Dept Ind & Syst Engn, Norman, OK 73019 USA
[2] Univ Oklahoma, Sch Civil Engn & Environm Sci, Norman, OK 73019 USA
关键词
Transportation network; Travel time; Optimal maintenance scheduling; Prioritization; Optimization; PARTICLE SWARM OPTIMIZATION; GENETIC ALGORITHM; RELIABILITY; PROBABILITY; PERFORMANCE; HEURISTICS; CRITERIA; DESIGN; COST;
D O I
10.1016/j.strusafe.2017.05.001
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This study develops a decision model to assist bridge authorities in determining a preferred maintenance prioritization schedule for a degraded bridge network in a community that optimizes the performance of transportation systems within budgetary constraints at a regional scale. The study utilizes network analysis methods, structural reliability principles and meta-heuristic optimization algorithms to integrate individual descriptive parameters such as bridge capacity rating, condition rating, traffic demand, and location of the bridge, into global objective functions that define the overall network performance and maintenance cost. The performance of the network is measured in terms of travel time between all possible origin-destination (O-D) pairs. In addition to the global budgetary constraint, the optimization is also conditioned on local constraints imposed on traffic flow by insufficient load carrying capacity of deficient bridges. Uncertainties in traffic demands, vehicle weights and maintenance costs are also considered in the problem formulation. Two project priority indices are introduced the static priority index (SPI), defined as a function of the difference in network travel time between block running (with reduced load carrying capacity before repair) and smooth running (design-level load carrying capacity after repair) of a bridge, and the dynamic priority index (DPI) defined as the likelihood of a bridge being selected for repair when the budget is fixed and the uncertainties governing the performance of the transportation network are considered. Finally, this decision model is illustrated with a hypothetical network with 160 bridges. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:96 / 104
页数:9
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