The Price of Uncertainty: New Asset Management Planning Models and Numerical Results

Currently there is a true dichotomy in the pavement asset maintenance and rehabilitation (M&R) literature. On the one hand, there are integer programming-based models that assume that parameters are deterministically known. On the other extreme, the authors have stochastic models that are based on the theory of Markov decision processes. In this paper wthe authors present an approach that is based on integer programming, but at the same time accounts for parameter uncertainties. Unlike virtually all existing stochastic models, the authors do not use the theory of Markov decision processes, i.e., othe authors model is non-Markovian. Another critical feature of the proposed models is that they provide probabilistic guarantees a priori that the prescribed M&R decisions would result in pavement condition scores that are above their critical service levels, using minimal assumptions regarding the sources uncertainty. By construction of the proposed models, the authors can easily determine the additional budget requirements when additional sources of uncertainty are considered, i.e., the price of uncertainty. A numerical case study presents valuable insights into the price of uncertainty and shows that the price of uncertainty can be large.

Language

  • English

Media Info

  • Media Type: DVD
  • Features: Figures; References; Tables;
  • Pagination: 15p
  • Monograph Title: TRB 89th Annual Meeting Compendium of Papers DVD

Subject/Index Terms

Filing Info

  • Accession Number: 01152384
  • Record Type: Publication
  • Report/Paper Numbers: 10-1179
  • Files: TRIS, TRB
  • Created Date: Jan 25 2010 10:31AM