Hub location problem is of new issues and branch of location problems, which is presented in recent decades. Hub location problem is flow traortation from the origin to the destination. In the network hub instead of a direct connection between both the origin and destination, flow are traorted through the hubs. In this study, a network hub and spoke are designed for air traort, where the sum of the travel times and waiting times at hubs is considered simultaneously. To calculate the waiting time at hubs, each hubs is considered as open Jackson network, including four components of M/M/c queuing systems, consisting; landing, unloading areas, loading areas and take off. Flow passing through each hub are separated to input and output flows from them. Optimum arrival rate to each hub and then the average waiting time at each hub is done with the location of hubs and allocation non-hub simultaneously. The proposed model is a mixed integer nonlinear programming. Due to the complexity of the model, the exact solution will be found a long time, so metaheuristic methods including genetic and particle swarm optimization algorithms is used to solve the proposed model. Also, the performance of the metaheuristic algorithms is compared. In this study also is used fuzzy approach to proposed model. The demand between nodes is considered as fuzzy variables. This problem is modeled with chance-constrained programming. For solving chance-constrained programming is used fuzzy simulation based genetic algorithm.