Immune algorithms-based approach for redundant reliability problems with multiple component choices

This paper considers the series-parallel redundant reliability problems in which both the multiple component choices of each subsystem and the redundancy levels of every selected component are to be decided simultaneously so as to maximize the system reliability. The reliability design optimization problem has been studied in the literature for decades, usually using mathematical programming or heuristic optimization approaches. The difficulties encountered for both methodologies are the number of constraints and the difficulty of satisfying the constraints. A penalty-guided immune algorithms-based approach is presented for solving such integer nonlinear redundant reliability design problem. The results obtained by using immune algorithms-based approach are compared with the results obtained from 33 test problems from the literature that dominate the previously mentioned solution techniques. As reported, solutions obtained by the proposed method are better than or as well as the previously best-known solutions.