An augmented Lagrangian decomposition approach for infrastructure maintenance and rehabilitation decisions under budget uncertainty

Abstract

This article addresses a general class of infrastructure management problems raised in maintenance and rehabilitation scheduling. Infrastructure agencies usually face budget uncertainties that eventually lead to suboptimal scheduling planning if maintenance decisions are made without taking the uncertainty into consideration. It is important for decision makers to adopt maintenance and rehabilitation scheduling policies that consider all budget scenarios. The authors propose a multistage, stochastic programming model to address this problem. The authors also develop a solution procedure using the augmented Lagrangian decomposition algorithm. A case study exploring the computational characteristics of the proposed algorithm is conducted and the benefit ofusing the stochastic programming approach is discussed.