In most of the previous studies, systems just had irreparable components or reparable components; in this article, a series-parallel system is considered that in which the components inside the subsystems can be non-repairable or repairable. The concept of availability is used for optimizing such a system and the main objection of solving the presented model is optimizing the availability of the system along with minimization of costs according to the weight and size restrictions. Although redundancy allocation problems are in the NP-Hard problems that increasing problem size, limitations, and new assumptions result in increasing their complexity, for solving these problems in great size exact methods cannot be used and meta heuristics methods such as genetic algorithm is used. Algorithm used in this study is Non-dominated Sorting Genetic Algorithm. In addition, for investigating implications and accuracy of the proposed model and the power of solution, results are compared with results of Gams software. Comparing the results of meta-inventive algorithm and Gams software, the conclusion was that the results had minor differences whereas the meta-inventive algorithm solution speed is much higher and it is evident that the power of meta-inventive methods is more that exact methods in solving NP-Hard problems. Moreover, comparing hypotheses of this thesis and hypotheses in the literature, it has been confirmed that in the combined state of repairable and irreparable components of this thesis, availability has increased and cost has decreased.
