(1. Key Lab of Department of Education and Hunan Province, Changsha University of Science & Technology, Changsha, Hunan 410114, China; 2. Institute of Bridge Engineering, Hunan University, Changsha, Hunan 410082, China)
Improved indirect maintenance cost models induced by maintenance action were developed. Based on a modified deterioration model of deteriorating wearing surfaces, a series of computational formulas under combinative maintenance scenario are derived to construct a multi-objective combinative maintenance planning model. The adaptive particle swarm optimization is used to optimize the optimal maintenance scenario by minimization of life-cycle maintenance cost and maximization of the structural performance satisfying the requirements of condition index and investment budget. A numerical example of deteriorating wearing surface is employed to demonstrate the effectiveness and usefulness of the proposed multi-objective maintenance planning optimization model. It is found that reasonable timing planning of time-controlled maintenance interventions can balance the life-cycle maintenance cost and condition level of deteriorating wearing surfaces.
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