Reliability optimization of complex systems using modified random-to-pattern search algorithm

The modified random-to-pattern search (MRPS) algorithm, developed by the authors for global optimization, is applied to find the global optimum of system cost of a complex system subject to constraints on system reliability. The global optimum solutions obtained by MRPS are compared with those obtained by employing gradient techniques as well as random search-based methods from the literature to solve the same problems. Results clearly indicate that the proposed MRPS algorithm is more robust and efficient in overcoming difficulties associated with local optima and the need for a starting solution vector.