Managing Pavement Maintenance and Rehabilitation Projects under Budget Uncertainties

A well-developed and maintained pavement management system (PMS) empowers a decision maker to select the best maintenance program, i.e., which maintenance treatment to use and where and when to apply it, so that a maximum utilization of available resources can be achieved. This paper addresses a decision making problem for managing pavement maintenance and rehabilitation projects under budget uncertainty (MPMRPBU). A stochastic linear programming model is formulated and solved for the MPMRPBU so that a set of candidate projects can be optimally selected from the highway network over a planning horizon. Numerical results are discussed based upon a pilot case study. Different optimization solutions based on deterministic optimization and stochastic programming approaches are discussed and compared. The effect of the budget constraint on the optimized solutions is investigated. The computational result indicates a high quality MPMRPBU solution using stochastic programming approach, suggesting that there is a potential that the algorithm can be used for real world applications.

摘要： 一个得到良好开发和维护的路面管理系统（PMS）能够帮助管理者做出在什么时候，对哪些路段采用什么样的路面维护和修复方案的决定，从而实现可用资源的最大化.本文提出一种在资金预算不确定条件下路面维护和修复项目管理决策优化方法(MPMRPBU)，为确保管理者在一个决策规划时段内，从公路网中选择并优化一组路面维护和修复方案，建立随机线性规划模型求解MPMRPBU问题.通过案例分析，比较在确定性优化和随机规划两种不同条件下的优化方案，研究不同经济预算对优化方案的影响.结果表明，采用随机规划方法能产生高质量的MPMRPBU解决方案, 该算法可以解决实际问题.