Abstract
Reward criterion is an important decision factor in a Markov-based road maintenance optimization model. At present, average reward criterion or discounted reward criterion is widely used to optimize life cycle costs of road maintenance. However, the former one cannot reflect the time value of life cycle costs whereas the latter one tends to neglect the costs accumulated in the later periods over the decision horizon. In this regard, a weighted reward criterion is developed for the Markov-based road maintenance optimization model. It measures the trade-off of the average reward and the discounted reward by setting the weights of two rewards. In addition, the existence of the optimal plan under the weighted reward criterion is proven by two numerical examples under two scenarios with and without considering the inflation on maintenance costs. Finally, comparison is conducted between the proposed criterion and the average reward criterion/the discounted reward criterion to check the impacts of discount rates and inflation rates on the optimal plan.
Highlights
To provide and distribute desired services of a road project, it is important to maintain road pavements in a good or at least serviceable performance over its service life
A road maintenance decision is a trade-off that balances the improvement of pavement performance and the expenditures of maintenance actions over the service life of a road project
The results show that the model using the developed weighted reward criterion will converge to the model using the average reward criterion if the decision horizon tends to be infinite
Summary
To provide and distribute desired services of a road project, it is important to maintain road pavements in a good or at least serviceable performance over its service life. A road maintenance decision is a trade-off that balances the improvement of pavement performance and the expenditures of maintenance actions over the service life of a road project. Based on the pavement deterioration modelling, the decision of road maintenance can be figured out in terms of the Markov decision process (MDP). In existing MDP models for road maintenance, the average reward criterion (Smilowita and Madanat 2000; Madanat et al 2006) or the discounted reward criterion (Jiang et al 2000; Guillaumot et al 2003) is the commonly used reward criterion to find the optimal life cycle costs. A weighted reward criterion, which considers both the average reward and the discounted reward, is developed for the Markov-based road maintenance optimization models over a finite decision horizon and an infinite decision horizon.
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