Pavement Maintenance Optimization Model using Markov Decision Processes

• Main Authors: Mandiartha, Putu, Duffield, C. F., Intan Suhana, Mohd Razelan, Azlina, Ismail
• Format: Article
• Language: English
• Published: IOP Publishing 2017
• Subjects: TA Engineering (General). Civil engineering (General); TE Highway engineering. Roads and pavements
• Online Access: http://umpir.ump.edu.my/id/eprint/18631/2/Mandiartha_2017_J._Phys.__Conf._Ser._890_012104.pdf; http://umpir.ump.edu.my/id/eprint/18631/; https://doi.org/10.1088/1742-6596/890/1/012104
• Institution: Universiti Malaysia Pahang

This paper presents an optimization model for selection of pavement maintenanceintervention using a theory of Markov Decision Processes (MDP). There are some particular characteristics of the MDP developed in this paper which distinguish it from other similar studies or optimization models intended for pavement maintenance policy development. These unique characteristics include a direct inclusion of constraints into the formulation of MDP, the use of an average cost method of MDP, and the policy development process based on the dual linear programming solution. The limited information or discussions that are available on these matters in terms of stochastic based optimization model in road network management motivates this study. This paper uses a data set acquired from road authorities of state of Victoria, Australia, to test the model and recommends steps in the computation of MDP based stochastic optimization model, leading to the development of optimum pavement maintenance policy.