Article ID: | iaor20091286 |
Country: | United Kingdom |
Volume: | 40 |
Issue: | 3 |
Start Page Number: | 205 |
End Page Number: | 222 |
Publication Date: | Mar 2008 |
Journal: | Engineering Optimization |
Authors: | Garcia-Diaz A., Yoo J. |
Keywords: | scheduling, optimization, lagrange multipliers, programming: branch and bound, programming: dynamic, construction & architecture |
An optimization methodology is developed for determining the most cost-effective maintenance and rehabilitation (M&R) activities for each pavement section in a highway pavement network, along an extended planning horizon. A multi-dimensional 0–1 knapsack problem with M&R strategy-selection and precedence-feasibility constraints is formulated to maximize the total dollar value of benefits associated with the selected pavement improvement activities. The solution approach is a hybrid dynamic programming and branch-and-bound procedure. The imbedded-state approach is used to reduce multi-dimensional dynamic programming to a one-dimensional problem. Bounds at each stage are determined by using Lagrangian optimization to solve a relaxed problem by means of a sub-gradient optimization method. Tests for the proposed solution methodology are conducted using typical data obtained from the Texas Department of Transportation.