The optimization of aviation networks is of great significance for optimizing the allocation of resources, improving transport efficiency, and enhancing the competitiveness among airline companies. There have been a lot of researches which combine the theory of complex network and the actual situations to analyze the air transportation system. The present work provides a certain theoretical basis for the plan of airline schedule. Firstly, we regard an airport as a node, flight frequency as a link weight, and build a heterogeneous network. Through empirical analysis, we find that the aviation network has small-world and scale-free properties. In addition, considering that the instant network consists of current flights changing over time, time-varying is another important characteristic of aviation network. Also, a spatiotemporal correspondence between the flight frequency and route geometric distance is demonstrated to be τij~rij-C. Secondly, by Monte Carlo simulation, we know that the time-ordered topologies influence the optimal navigation structure and make it different from those from traditional static models. Specially, we can obtain a unique restriction between C and optimal structural exponent α, which unveils a new optimization principle in route design and schedule arrangement. Applying these features to the cost-minimized optimization model, a method to evaluate the optimization of network is proposed, by which we can directly predict the overall optimal distribution of flight distances and corresponding flight frequencies only based on the information about the passenger flow assignment. Thirdly, China aviation network data from 2001 to 2010 are used for empirical study. It is found that the predictions consist with the actual data. Compared with traditional optimization methods, it can simplify the computational complexity, and therefore it takes full advantage of the structural convenience and provides a new perspective for the overall scheduling of air transportation system. In this case, companies are able to estimate route adjustments easily to see whether they are reasonable and analyze the development trend of network to provide suggestions for future optimization.