A Robust Optimization Approach to Resources Allocation in Maintained Systems

Optimization of maintenance resources to maximize the system availability is a major concern in different manufacturing systems. Therefore, a lot of effort is put to construct optimization models to reach the maximum availability level and to reduce the costs of lack of availability. However, despite these efforts, data uncertainty in the real world problems was neglected in proposed models which results models with sophisticated nonlinear constraints. In this article the budget uncertainty model of optimization is considered and its counterpart in resources allocation for maintained systems is presented. The proposed model takes into account the degrees of conservativeness to introduce a robust model of optimization. This model is capable of maximizing the availability for the maintained system under certain conditions. The capability of the model in controlling the effects of uncertainty is investigated by means of simulation studies and reasonable results concluded.