Bi-objective Reliability Optimization of Switch-Mode k-out-of-n Series-Parallel Systems with Active and Cold Standby Components Having Failure Rates Dependent on the Number of Components.

This paper discusses a bi-objective reliability optimization of a switch-mode active and cold standby k-out-of-n series-parallel system in which a switch is installed to add a redundant component when one of the components fails. The system failure rate is not only dependent on the number of its working components, but reduces when more monitory resources are allocated. As the bi-objective optimization problem is shown to belong to the class of NP-hard problems, a multi-objective meta-heuristic algorithm, namely multi-objective evolutionary algorithm based on decomposition (MOEA/D) with a novel solution structure is developed to solve large-scale problems. Since there is no benchmark available in the literature, the well-known multi-objective evolutionary algorithm called the non-dominated sorting genetic algorithm (NSGA-II) is utilized to validate the solutions obtained. The parameters of both algorithms are tuned by the Taguchi method where the AHP-TOPSIS method is applied to compare the performances of the parameter-tuned algorithms in terms of several multi-objective performance measures. The results are in support of MOEA/D. [ABSTRACT FROM AUTHOR]