ABSTRACT
Decision makers have different attitudes towards risks and opportunities of maintenance and rehabilitation (M&R) strategies. However, most existing pavement management studies simply assumed the neutral attitudes of decision makers. The available risk-based network-level M&R optimisation research equated risk with uncertainty which is actually different. Hence, this study aims to develop a method to quantitatively incorporate decision makers’ attitudes towards risk and opportunity into network-level pavement maintenance planning. Quantitative criteria were developed and incorporated into the maintenance optimisation model. A multi-objective optimisation (MOO) model was established to explore the trade-offs between expected returns, risks, and opportunities. The proposed methods were applied to a real-world highway network as a demonstration. The results show that budget increases can simultaneously reduce expected total costs and downside risks and increase upside potential by up to 0.41%, 5.26%, and 0.92%, respectively, for each 1% increase in current year’s budget, but their marginal effects are diminishing. Risk reduction requires compromising the expected performance and upside potential of the M&R strategy. The solutions derived from the mean-semivariance model dominate those from the mean-variance model. The outcomes of this study provide decision-makers with ways to incorporate their attitudes into maintenance optimisation, thereby reducing risk exposure and exploiting potential opportunities.
Acknowledgements
This study was conducted under the support of the Research Institute for Sustainable Urban Development (RISUD) at the Hong Kong Polytechnic University. In addition, the data used in this research were collected from the Pavement Management System in Jiangsu province, China. The engineers and researchers who built the system and collected the data are also acknowledged for their contribution.
Disclosure statement
No potential conflict of interest was reported by the author(s).