PARTICLE SWARM ALGORITHM-BASED MULTI-OBJECTIVE COMBINATIVE OPTIMIZATION OF MAINTENANCE SCENARIOS FOR DETERIORATING WEARING SURFACES

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.