Maximization of system availability with failure dependency
Résumé
System availability optimization is one of the most challenging problems for modern complex systems. Basically, availability can be enhanced by increasing redundant components and the set of available maintenance teams which may lead to a dramatic increase in the overall system cost. In this context, this paper proposes an efficient optimization approach to get the best system design of series k - out - of - n : G system achieving the maximal possible steady system availability. A maximum system cost constraint should not be exceeded. The system cost is assumed composed of components purchase cost and repair cost. Moreover, since dependency is essential for reliability optimization problems, the redundant dependency which is a specific kind of failure dependency is taken into account. To solve the optimization problem, a resolution approach based on Genetic Algorithms (GA) is presented. Finally, a numerical application is carried out. The GA results are compared with the results given by LINGO which is a dedicated optimization software. It is used to validate the efficiency of the proposed approach.