A Methodology to Determine Non-Fixed Performance Based Thresholds for Infrastructure Rehabilitation Scheduling

In an era of increasing demand and loading, aging infrastructure, and funding shortfalls, infrastructure agencies continue to seek cost-effective solutions to persistent and pervasive questions regarding the upkeep of their physical assets. One such question is the appropriateness of the current fixed condition thresholds used at several agencies for rehabilitation timing purposes, whether there is the possibility of having flexible rather than fixed thresholds, and determining what these thresholds should be. A related question is how these flexible thresholds may vary, depending on the objectives of the decision maker, the relative weight of agency and user costs, and the form of expression of the life-cycle cost associated with the candidate rehabilitation schedules. Fortunately, a number of past researchers have developed inputs that are valuable for addressing this issue. Also, there exists data from in-service infrastructure that could be used to test the hypotheses regarding the sensitivity of the optimal schedules. This dissertation developed a methodology to address this research question. This was done for two constraint scenarios related to the direction of successive threshold levels: unrestricted and restricted. In order to optimize the rehabilitation schedules (strategies), the objective was to maximize the cost-effectiveness ratio, expressed as the change of the cost effectiveness of a candidate strategy schedule compared to that of the do-nothing strategy. Cost was measured in terms of agency cost, user cost, or both, incurred during infrastructure downtime (workzones) or during normal infrastructure operations. Effectiveness (or benefits) was measured in terms of performance jumps, infrastructure service life, infrastructure average performance, the area bounded by the performance curve, agency cost savings, and user cost savings over the life of the infrastructure. For the life-cycle costs, three interest rates and two alternative life-cycle cost expressions were used; the present worth cost over a given service life or to perpetuity, and the equivalent uniform annual cost over a given service life or to perpetuity. The results of the analysis suggest that, compared to the restricted scenario, the optimal strategies developed using the unrestricted scenario yield superior objective function levels irrespective of the cost-effectiveness criteria, cost weight ratio, or life-cycle cost expression used in the analysis. The results for restricted and unrestricted scenarios provided valuable insight. For the unrestricted scenario, the developed optimal strategies indicate that the subsequent rehabilitations should be applied at condition levels successively superior to the condition at the time of the previous rehabilitation; whereas the restricted scenario yielded the opposite trend: interventions are triggered when the infrastructure is in a condition worse than the previous intervention. This seems to reflect a tradeoff: while the unrestricted scenario generally yields superior cost-effectiveness values, its practical implementation may face obstacles from a public relations viewpoint. This is because the strategies offered by the restricted scenario (successively lower thresholds) gradually anticipate the infrastructure users to be increasingly tolerant of successively lower levels of service. From the case study, it was also found that the optimal solutions developed using certain cost-effectiveness criteria such as the performance jump, agency cost and user cost savings are less sensitive to life-cycle cost expression and cost component weights compared to other criteria. Finally, this dissertation discussed the consequences of hastened or deferred rehabilitations with respect to an optimal strategy. It was found that deferring rehabilitation has greater adverse consequences than hastening rehabilitation