Abstract
This article develops an optimization framework for scheduling a programmable preservation activity for an infrastructure (primary) system that accounts for a specific context of interdependency between its maintenance phase and the operations phase of a neighboring (secondary) system. The framework identifies the optimal deterioration threshold of the primary system for the preservation activity, subject to a disruption in the operations of the neighboring system. The methodology also includes trade‐off analysis using a biobjective genetic algorithm approach to accommodate the conflicting objectives associated with the costs and benefits of the programmed preservation activity. The framework provides decision makers with optimal/near optimal Pareto frontiers of the primary system's preservation activity candidate thresholds based on the costs and benefits associated with each candidate. The article demonstrates the developed framework using a case study involving colocated pavement and underground utility systems. The results of the case study show that it is feasible to use the developed framework to identify the optimal preservation activity timing for an infrastructure system whose level of service is subject to disruptions from a neighboring system. Overall, the results demonstrate that a disruptive event caused by a secondary system could influence the Pareto optimal solutions (activity thresholds) associated with the timing of a primary system's preservation activity. The article validates the optimal solution by comparing the results with those obtained using the exact method.