Optimization of Linear Consecutive-k-Out-of-n Systems with Birnbaum Importance Based Ant Colony Optimization Algorithm

The linear consecutive-k-out-of-n: failure (good) (Lin/Con/k/n:F(G)) system consists of n interchangeable components that have different reliabilities. These components are arranged in a line path and different component assignments change the system reliability. The optimization of Lin/Con/k/n:F(G) system is to find an optimal component assignment to maximize the system reliability. As the number of components increases, the computation time for this problem increases considerably. In this paper, we propose a Birnbaum importance-based ant colony optimization (BIACO) algorithm to obtain quasi optimal assignments for such problems. We compare its performance using the Birnbaum importance based two-stage approach (BITA) and Birnbaum importance-based genetic local search (BIGLS) algorithm from previous researches. The experimental results show that the BIACO algorithm has a good performance in the optimization of Lin/Con/k/n:F(G) system.