Abstract
The rapid advancements in science and technology aggravate the need for the optimal design of modern systems, aiming to achieve the maximum system reliability while meeting some resource constraints (e.g., cost, weight, etc). In this paper, we consider the system reliability optimization for series-parallel systems subject to common-cause failures (CCF). Unlike traditional approaches that consider either cold or hot standby redundancy for a parallel subsystem, our approach considers a combination of cold and hot standby redundancy within one subsystem to achieve a balance between fast recovery and power conservation in the optimal system design. A new problem formulation to incorporate CCF is proposed. For problem formulation, an analytical method combined with an existing combinatorial method is proposed to generate the objective function that evaluates the reliability of a subsystem with both hot and cold standby units and subject to CCF. The method has no limitation on the type of time-to-failure distributions for the system components. An optimization solution methodology based on genetic algorithm is presented for obtaining an optimal design configuration with maximum system reliability while satisfying some system-level cost constraint. The proposed methodology is tested on several example data sets and the corresponding reliability optimization results are presented. [PUBLICATION ABSTRACT]