Abstract

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.

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