Multi-objective optimization for k-out-of-n redundancy allocation problem

The multi-objective optimization for k-out-of-n redundancy allocation problem with multiple k-out-of-n subsystems connected in series considering k impacts the cost function is presented. The design objective is to select multiple components for a subsystem to maximize system reliability and minimize system cost while satisfying system requirement constraints. Mixing of non-identical component types is allowed in each subsystem as well as at system level. In the design process, component selection and k value are considered as decision variables for each subsystem. In practice, different values of k and component selection provided different design choices. In this paper, k impacts the cost function. To reduce the system design cost, multiple low-cost components may be preferred, because they are cheaper than a highly reliable component that has unaffordable cost. In this case, k >; 1 is considered, when multiple low-cost components are required to function in a subsystem. The approach is demonstrated on a test problem with interesting results. A Genetic algorithm is effectively applied to solve the multi-objective optimization problem.