@article { author = {Nasri, Paria and Massihi, Ellips and Mousavi, Seyed Javad and Teymoori, Mohammad}, title = {A Fuzzy Expert System for Policy Making on Roads Pavement Maintenance}, journal = {Advances in Industrial Engineering}, volume = {51}, number = {4}, pages = {449-462}, year = {2017}, publisher = {University of Tehran}, issn = {2783-1744}, eissn = {2783-1744}, doi = {10.22059/jieng.2017.227967.1329}, abstract = {Roads are one of the fundamental infrastructures for nations’ development, and their maintenance is of utmost importance. However, roads are subject to gradual deterioration due to vehicles’ continual run, climate change, and miscellaneous damages. Hence, road management centers in various countries, design and analyze a range of maintenance policies depending on road conditions through continuous monitoring. While deciding the time and type of road maintenance, has been traditionally done selectively by experts, regarding the large number of fragments in road networks, repeated and non-algorithmic nature of the decision making process, as well as the need for high precision to avoid over-budgeting, this task should be performed preferably by means of decision support systems. In order to determine appropriate actions for maintaining road fragments, pavement assessment indices must be measured at first, and then the right policy for maintaining each fragment or the whole road network must be planned based on the estimated maintenance costs and the allocated budget. In this paper, a fuzzy expert system is developed as a decision support system to assist road maintenance managers in their decision process by enhancing the speed and precision of policy making.}, keywords = {Expert system,Fuzzy inference engine,Pavement management,Road maintenance policy}, url = {https://aie.ut.ac.ir/article_65128.html}, eprint = {https://aie.ut.ac.ir/article_65128_8981279bfb2d11862ea7aa363b1c099a.pdf} }