| Paper title: |
A Model of Costs Simulation using Monte Carlo Method for Road Pavement Development Projects |
| DOI: | https://doi.org/10.4316/JACSM.201902001 |
| Published in: | Issue 2, (Vol. 13) / 2019 |
| Publishing date: | 2019-12-16 |
| Pages: | 9-13 |
| Author(s): | ARBA Raluca |
| Abstract. | Road pavement construction projects are a complex type of project that involve a considerable amount of resources and time, which leads in many cases in a considerable increase of costs. Therefore risk and uncertainty are variables that may lead to significant changes in the budget of a project and may even lead to failure unless these changes are taking into consideration when determining the budget. This paper aims to present a model of cost simulation using the Monte Carlo Method which takes into consideration the main road parameter that may cause failure of a project – type of road distress, the level of failure and its impact on final budget of a project. |
| Keywords: | Impact On Costs, Simulation, Monte Carlo Method, Road Pavement Projects |
| References: | 1. R Arba, S Jecan, L Rusu, DA Sitar-Taut, monte carlo simulation method for risk management in road pavement maintenance projects, Environmental Engineering and Management Journal, August 2019, Vol. 18, No. 8, P. 1639-1646 2. Benta, D., Jecan, S., Rusu, L. & Dines, O., (2017) Business Process Analysis for Risk Management in PAV3M. Environmental Engineering & Management Journal (EEMJ), 16(4), pp. 949-956. 3. Fang, C. & Marle, F., (2011) A Simulation-Based Risk Network Model for Decision Support in Project Risk Management. Decision Support Systems,Elsevier.. 4. Herbold, K., (2000) Using Monte Carlo Simulation for Pavement Cost Analysis. Public Roads, Issue No: Vol. 63 No. 4. Retrieved from Issue No: Vol. 63 No. 4 . 5. Miller, J. & Bellinger, W., (2003) Distress identification manual for the long-term pavement performance program, Washington D.C.: Federal Highway Administration Report FHWA-RD-03-031. 6. Miller, J. & Bellinger, W., (2014) Distress Identification Manual for Long Term Pavement Performance Program, Washington D.C.: United States Federal Highway Administration. Office of Infrastructure Research and Development. 7. Mills, L., Attoh-Okine, N. & McNeil, S., (2012) Hierarchical Markov Chain Monte Carlo Simulation for Modeling Transverse Cracks in Highway Pavements. Journal of Transportation Engineering, Volume 138 Issue 6., pp. 700-705. 8. Patchin, C. & Mark, C., (2012) Risk Assessment in Practice. , Retrieved from deloitte.com: https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Governance-Risk-Compliance/dttl-grc-riskassessmentinpractice: Deloitte & Touche LLP. 9. Rusu, L., Benţa, D., Podean, M. & Arba, R., (2012) Web Based Pavement Maintenance and Monitoring System. Procedia Technology, Elsevier, , pp. 74-83. 10. Rusu, L., Sitar-Taut, D. & Jecan, S., (2015) An integrated solution for pavement management and monitoring systems. Procedia Economics and Finance, Elsevier, Volume 27, pp. 14-21. 11. Stoneburner, G., Goguen, A. & A., F., (2002) Risk Management Guide for Information Technology System. National Institute of Standards and Technology, Special Publication 800-30, p. 1., s.l.: National Institute of Standards and Technology, Special Publication 800-30. 12. Walls, J. & Smith, M., (1998) Life-Cycle Cost Analysis in Pavement Design, Washington D.C.: Report no. FHWA-SA-98-079, Federal Highway Administration USA |
| Back to the journal content | |
