Since the evaluation and improvement of components, machines and systems have a significant importance, many models have generated and solved for system reliability optimization based on state and type of systems. These models can extract an appropriate strategy for increasing the life cycle of system. To achieve this goal, different models with different solutions have been tested and evaluated. In assessment of related literature review, it would be conceived that the time of failures and the relevant time value of maintenance costs could be considered, but these parameters have not been inserted in optimization models. With this adjustment, the output strategy of optimization model, not only satisfy the system design moment but also it can cover the period of system operational time. Therefore, this work tries to eliminate the stated shortage from system reliability optimization models. After that, a numerical example would be solved by using Genetic Algorithm (GA) that is the most applicable meta-heuristic method in this field. At last, due to exhibit the capability of Imperialist Competitive Algorithm (ICA) for solving the system reliability optimization problems, the proposed model has been solved using this new meta-heuristic method.