Universal redundancy strategy for system reliability optimization

The redundancy allocation problem involves the selection of components and redundancy levels to maximize system reliability given various system-level constraints such as cost, weight and volume. We study a specific redundancy allocation problem in which redundancy strategies are also selected for each subsystem including active, standby, mixed and K-mixed. The main contribution of this paper consists of proposing a new universal redundancy strategy. In all existing strategies, the insertion of redundant components is triggered by some specific failures of operating components. The newly developed strategy provides the possibility to change the system structure at any time by inserting or removing redundant components individually or simultaneously. This strategy is said universal in the sense that it includes all previous strategies, while offering a wide range of possibilities by selecting the optimal reconfiguration instant, along with the optimal numbers of components to be activated or inactivated for each subsystem. A non-linear mixed-integer programming model is developed, and the resulting combinatorial optimization problem is solved by coupling a continuous time Markov chain model with a simulated annealing algorithm. Using numerical examples of a single subsystem and a well-known benchmark series-parallel system, the obtained results show the efficiency of the proposed strategy.