Return
A multi-year pavement maintenance program using a stochastic simulation-based genetic algorithm approach
DOI:10.1016/j.tra.2005.12.003.png)
Abstract
En 中文
The objective of this paper is to introduce a multi-year pavement maintenance programming methodology that can explicitly account for uncertainty in pavement deterioration. This is accomplished with the development of a simulation-based genetic algorithm (GA) approach that is capable of planning the maintenance activities over a multi-year planning period. A stochastic simulation is used to simulate the uncertainty of future pavement conditions based on the calibrated deterioration model while GA is used to handle the combinatorial nature of the network-level pavement maintenance programming. The effects of the uncertainty of pavement deterioration on the maintenance program are investigated using a case study. The results show that programming the maintenance activities using only the expected pavement conditions is likely to underestimate the required maintenance budget and overestimate the performance of pavement network. (c) 2005 Elsevier Ltd. All rights reserved.
Keywords:
pavement maintenance programming
simulation-optimization
genetic algorithms
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
T
IF:
6.8
Papers:
5.0K
Citations:
2.4W
Organization
No organization information available
Cited Papers
Efficient bioremediation of indigo-dye contaminated textile wastewater using native microorganisms and combined bioaugmentation-biostimulation techniques
Chemosphere
IF0
no more

