Risk based cost estimation of capital intensive road projects using Monte-Carlo simulation

This paper presents the application and validation of a new and innovative tool developed for accurate risk based estimation of project budgets. Typical capital intensive projects to which this tool can be applied include road reconstruction, road resheet and road rehabilitation projects. Quantitative risk analysis and stochastic modeling using Monte-Carlo Simulation is embedded in the algorithms of the computer code. The tool forecasts a range of possible project costs and the probability of the occurrence of those costs by taking into account uncertainties and associated risks. Application of the tool to capital intensive road projects designed by Harsha Ranade and constructed in 2011 & 2012 demonstrates the validity, usefulness and benefit of the proposed tool. Comparisons of forecasted estimates using this new tool with actual costs and with traditional deterministic methods of cost estimation (such as single-point base-case estimates inclusive of contingency) provide valuable insights that can aid management in evaluating alternatives and make informed decisions when estimating and allocating budgets to a portfolio of road projects.

• Authors:
  • Rao, M
  • Ranade, H V
• Conference:
  • International Public Works Conference, 2013, Darwin, Northern Territory, Australia
• Publication Date: 2013-8

Language

• English

Media Info

• Pagination: 25p
• Monograph Title: Public works: explore new territory: IPWEA International Public Works Conference, Darwin, NT, 11-15 August 2013

Subject/Index Terms

• TRT Terms: Budgeting; Costs; Highway maintenance; Highway operations; Highways; Maintenance; Mathematical models; Risk analysis; Risk assessment
• Uncontrolled Terms: Road design and asset management
• Geographic Terms: Melbourne (Australia)
• ATRI Terms: Budget; Modelling; Risk analysis; Road costs; Road maintenance; Road management
• ITRD Terms: 132: Forecast
• Subject Areas: Highways; Maintenance and Preservation; I10: Economics and Administration;

Filing Info

• Accession Number: 01495612
• Record Type: Publication
• Source Agency: ARRB
• Files: ITRD, ATRI
• Created Date: Oct 17 2013 10:09AM