Application of Artificial Intelligence for Optimization in Pavement Management
AbstractArtificial intelligence (AI) is a group of techniques that have quite a potential to be applied to pavement engineering and management. In this study, we developed a practical, flexible and out of the box approach to apply genetic algorithms to optimizing the budget allocation and the road maintenance strategy selection for a road network. The aim is to provide an alternative to existing software and better fit the requirements of an important number of pavement managers. To meet the objectives, a new indicator, named Road Global Value Index (RGVI), was created to contemplate the pavement condition, the traffic and the economic and political importance for each and every road section. This paper describes the approach and its components by an example confirming that genetic algorithms are very effective for the intended purpose.
T. F. Fwa, W. T. Chan, and K. Z. Hoque, "Network level programming for pavement management using genetic algorithms," Proc. 4th International Conference on Managing Pavements, pp. 815-829, May 1998.
K. J. Feighan, M. Y. Shahin, and K. C. Sinha, "A dynamic approach to optimization for pavement management systems," Proc. Second North American Conference on Managing Pavements, vol. 2, pp. 195-206, 1987.
T. Fwa, K. C. Sinha, and J. Riverson, "Highway routine maintenance programming at network level," Journal of Transportation Engineering, vol. 114, no. 5, pp. 539–554, September 1988.
W. D. Paterson and P. E. Fossberg, "Achieving efficiency in planning and programming through network-level policy optimization and pavement management," Proc. Second North American Conference on Managing Pavements, pp. 2.183-2.94, 1987.
R. Salini, "INTELLIPave - Uma AbordagemBaseadaemInteligência Artificial para a Modelagem de Pavimentos Asfálticos," Ph.D. thesis, Department of Computer Science, Univ. of Minho, Braga, 2010.
R. Salini, J. Neves, and A. Abelha, "Intellipave - considering aside failure criteria and unknown variables in evolutionary intelligence based models for asphalt pavement," Proc. 23rd European Conference on Modellingand Simulation, pp. 624-629, June 2009.
J. H. Holland, "Adaptation in Natural and Artificial Systems,"Ann Arbor, Michigan: University of Michigan Press, 1975.
D. E. Goldberg, "Genetic Algorithms in Search, Optimization and Machine Learning,"Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA, 1989.
K. Z. Hoque, C. W. Tat, and F. T. Fang, "Multi-objective programming for pavement management using genetic algorithms," Journal of the Eastern Asia Society for Transportation Studies, vol. 3, no. 3, pp. 117-132, September 1999.
R. L. Roper, "Using genetic algorithms to select optimum pavement treatment intervention strategies," Proc. 6th International Conference on Managing Pavements, 13 pages, October 2004.
J. Roberts, R. Roper, and A. Loizos, "PLATO: A new engine for the implementation of HDM technology for road infrastructure management analysis," Proc. 21st ARRB Transport Research Conference and 11th Road Engineering Association of Asia and Australasia (REAAA) Conference, 23 pages, 2003.
A. Golroo and S. L. Tighe, "Optimum genetic algorithm structure selection in pavement management," Asian Journal of Applied Sciences, vol. 5, no. 6, pp. 327-341, 2012.
T. Scheinberg and P. C. Anastasopoulos , "Pavement preservation programming: a multi-year multi-constraint optimization methodology," Proc. 89th Annual Meeting of the Transportation Research Board, 16 pages, 2010.
A. A. Elhadidy, E. E. Elbeltagi, and M. A. Ammar, "Optimum analysis of pavement maintenance using multi-objective genetic algorithms," Housing and Building National Research Center Journal, vol. 11, no. 1, pp. 107-113, April 2015.
C. Torres-Machí, A. Chamorro, C. Videla, E. Pellicer and V. Yepes, "An iterative approach for the optimization of pavement maintenance management at the network level," The Scientific World Journal, vol. 2014, 11 pages, 2014.
N. R. Tayebi, F. Moghadasnejhad and A. Hassani, "Analysis of pavement management activities programming by particle swarm optimization," ACEEE International Journal on Communication, vol. 2, no.1, pp. 22-27, March 2011.
ASTM, "Standard Practice for Roads and Parking Lots Pavement Condition Index Surveys," http://www.astm.org/Standards/D6433.htm, Feb. 11, 2015.
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