Reliability allocation model and algorithm for phased mission systems with uncertain component parameters based on importance measure

Highlights: • A model for reliability allocation problem of PMS with uncertainty is proposed. • A hybrid heuristic algorithm is presented based on a global importance index. • The effectiveness of the model and algorithm for PMS are demonstrated. • The efficiency of the algorithm can be improved by using component importance. This paper presents a model to deal with reliability allocation problem of phased mission systems (PMS), especially for PMS with uncertainty in components' parameters due to inaccurate information and different phase environments. In practice, real value of the reliability of a component may become lower than its designed value due to such uncertainty, thus making the whole system fail to meet the required reliability level. Therefore, in this paper, we present a model that incorporates the component uncertainty in the system reliability allocation process and then propose a variance-based global importance hybrid heuristic algorithm for its solution. The variance-based global importance measure is used to evaluate the importance of a component to the mission reliability of PMS while the reliabilities of all components vary randomly. The main procedures of the proposed algorithm include: (1) generate feasible solutions by roulette wheel selection method based on a global importance index; (2) improve solutions by adjusting reliability parameter values of components according to their global importance; and (3) improve solutions by crossover and mutation operations of genetic algorithm (GA). To illustrate the effectiveness of the proposed model and algorithm, two examples of PMS are presented and the allocation solutions are validated through Monte–Carlo simulation method. Finally, we compare the proposed model with a general allocation model that does not consider component uncertainty, and additionally with a cost-based heuristic algorithm and a particle swarm optimization (PSO) algorithm. Our results show that component uncertainty has significant influence on the confidence level that an allocation solution satisfies the required system reliability. Hence, it is essential to consider component uncertainty in reliability allocation process. In comparison with the cost heuristic algorithm and the PSO algorithm, the proposed algorithm is more effective in reliability allocation of PMS with uncertainty in components' parameters.