Details:

Creators:
Gao, Lu ; Zhang, Zhanmin ;
Gao, Lu ; Zhang, Zhanmin ; Less -
Corporate Creators:
University of Texas at Austin. Center for Transportation Research ;
Corporate Contributors:
Texas Transportation Institute ;
Subject/TRT Terms:
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Pavements--Maintenance And Repair--Management--Mathematical Models
Stochastic Analysis
Budgeting
Mathematical Models
Pavement Maintenance
Statistical Analysis
Stochastic Processes

Publication/ Report Number:
SWUTC/11/161028-1 ;
Resource Type:
Tech Report ;
Geographical Coverage:
Texas ;
OCLC Number:
755029545
Corporate Publisher:
Southwest Region University Transportation Center (U.S.) ;
NTL Classification:
NTL-HIGHWAY/ROAD TRANSPORTATION-Construction and Maintenance ; NTL-ECONOMICS AND FINANCE-ECONOMICS AND FINANCE ; NTL-PLANNING AND POLICY-PLANNING AND POLICY ; NTL-REFERENCES AND DIRECTORIES-Statistics ;
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 ;
Collection(s):
University Transportation Centers
US Transportation Collection
Main Document Checksum:
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urn:sha256:2923c630594a8408079fc31421ade00aedbc97eebd38f76e73efb1f2f0996458
File Type:

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