A bit-encoded heuristic evolutionary optimization algorithm inspired by the Generalized Extremal Optimization method is presented. The proposed evolutionary approach aims at optimizing a predictive maintenance scheduling problem characterized by an analytically intractable objective function. A preliminary comparison with a standard genetic algorithm on a set of high-dimension cases of the cons...

As a maintenance strategy to reduce unexpected failures and enable safe operation, condition-based (CBM) has been widely used in recent years. The decision criteria of CBM the literature mostly originate from statistical failure data or degradation states, few which can directly effectively reflect current state analyze condition monitoring data, measures, reliability together at same time. In ...

The paper deals with a development of the rolling horizon approach introduced recently for grouping maintenance strategies of multi-component systems by integrating two efficient optimization algorithms. The proposed approach can help to construct an optimal maintenance planning with a given availability constraint under limited repairmen. Thanks to the rolling horizon spirit, the maintenance p...

We introduce an approach for modelling the structural deterioration of components of bridges for maintenance optimization purposes. The Markov chain model is found in the maintenance and repair problems since the early 60's, is introduced to the maintenance of road infrastructure in the 1980's, and is made to drive the current bridge maintenance optimization systems. While this model results in...

In condition based maintenance (CBM) optimization, the main optimization objectives include maximizing reliability and minimizing maintenance costs, which are often times conflicting to each other. In this work, we develop a physical programming based approach to deal with the multi-objective condition based maintenance optimization problem. Physical programming presents two major advantages: (...