Optimal infrastructure maintenance scheduling problem under budget uncertainty.

Details

• Creators:
  Gao, Lu ; Zhang, Zhanmin
• Corporate Creators:
  University of Texas at Austin. Center for Transportation Research
• Corporate Contributors:
  Texas Transportation Institute
• Subject/TRT Terms:
  • Pavement maintenance
  • Mathematical models
  • Stochastic processes
  • Statistical analysis
  • Budgeting
  • Pavements--Maintenance and repair--Management--Mathematical models
  • Stochastic analysis
• Publication/ Report Number:
  SWUTC/11/161028-1
• Resource Type:
  Tech Report
• Geographical Coverage:
  Texas
• Corporate Publisher:
  Southwest Region University Transportation Center (U.S.)
• Abstract:
  This research addresses a general class of infrastructure asset management problems. Infrastructure ; agencies usually face budget uncertainties that will eventually lead to suboptimal planning if ; maintenance decisions are made without taking the uncertainty into consideration. It is important for ; decision makers to adopt maintenance scheduling policies that take future budget uncertainty into ; consideration. The author proposes a multistage, stochastic linear programming model to address this ; problem. The author also develops solution procedures using the augmented Lagrangian ; decomposition algorithm and scenario reduction method. A case study exploring the computational ; characteristics of the proposed methods is conducted and the benefit of using the stochastic ; programming approach is discussed.
• Format:
  PDF
• Funding:
  10727
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/23105/dot_23105_DS1.pdf
• File Type:
  [PDF - 521.42 KB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:8ae0b131a9058d9e6ead62c91de969bb98de21d611f85da646915124a11da651dab2b76a7b4d9fafa83282bd850404f1ec298012ef0bdfeea0c820d3c1e9795b