System reliability optimization with constraint k-out-of-n redundancies

A system reliability optimization approach with multiple k-out-of-n subsystems connected in series is presented. The design objective is to select multiple components to maximize system reliability while satisfying system requirement constraints such as cost and weight. Mixing of non-identical component types is allowed in each subsystem as well as at the system level. In practice, different design configurations can be associated with different values of k. Thus k is considered a decision variable selected as part of the design process. Previously, k was generally considered to be one to maximize the system reliability. In this paper, k impacts the cost function, and k >; 1 is considered. When k >; 1, components with relatively low reliability may be selected to satisfy the system cost constraint. The approach is demonstrated on a well-known test problem with interesting results. A genetic algorithm is effectively applied to solve the optimization problem.