An Importance Based Algorithm for Reliability-Redundancy Allocation of Phased Mission Systems
In engineering applications, there are systems that have both newly developed components with optimized reliability parameters and existed components with fixed reliability parameters. The reliability-redundancy allocation problem (RRAP) is raised to solve these cases by simultaneous optimizing components reliability and providing redundant components. However, most of the existed literature does not consider this kind of systems and they mainly focuses on series-parallel system, this paper propose a hybrid heuristic measure to solve RRAP of phased mission systems (PMS). Importance analysis can estimate the relative importance of components to system reliability, and provide useful information for reliability allocation or redundancy allocation for improving system performance. In this study, an importance based heuristic algorithm is hybridized with well-known genetic algorithm (GA). By embedding the reliability-importance based local search operator in standard GA, the local exploration ability has been further improved. Two PMS examples are presented and the results are compared with standard GA to validate the effectiveness of the provided algorithm.