Abstract
ABSTRACT Infrastructure asset management is concerned with the efficient and sustainable utilization of resources. There are numerous sources of uncertainties associated with the physical state of the infrastructure, climate change, and the economy. Thus, the most appropriate decision-making process to select maintenance and replacement strategies that are sustainable, economical, and safe should also be well informed in terms of risks. The decision process is formulated as a multi-objective optimization problem and exemplified the case for targeted performance levels and total costs, and solved using both Multi-Objective Particle Swarm Optimization (MOPSO) and a Non-dominated Sorting Genetic Algorithm II (NSGA-II). The results indicate that annual budget constraints have a significant effect on the Pareto front and the schedule associated with individual solutions. The proposed approach provides a useful and flexible decision-analysis tool for managers by allowing for multiple objective optimization in scheduling future interventions towards the sustainability of infrastructure.
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