IAs based approach for reliability redundancy allocation problems

Nonlinearly mixed-integer reliability design problems are investigated in this paper where both the number of redundancy components and the corresponding component reliability in each subsystem are to be decided simultaneously so as to maximize the reliability of system. The reliability design problems have been studied in the literature for decades, usually using mathematical programming or heuristic/metaheuristic optimization approaches. The difficulties confronted for both methodologies are to maintain feasibility with respect to three nonlinear constraints, namely, cost, weight and volume related constraints. A penalty guided artificial immune algorithm is presented for solving such mixed-integer reliability design problems. It can search over promising feasible and infeasible regions to find the feasible optimal/near optimal solution effectively and efficiently. Numerical examples indicate that the proposed approach performs well for the reliability-redundant allocation design problems considered in this paper. As reported, solutions obtained by the proposed approach are as well as or better than the previously best-known solutions.