Airlines utilize hub-and-spoke networks in order to benefit their economies of scale. But, according to flow centralizations, some hub airports get congested especially in rush hours and number of delayed flies increases remarkably. Common capacitated hub location models cannot prevent this adverse outcome. In order to handle this problem, this study considers runways of airports as an M/G/1 queuing system, individually. Also, triple derivative models for obtaining optimal capacity of landing, takeoff, and hybrid runways are proposed. The final optimal capacity in the final model guarantees the average desirable delays and presence of a determined number of planes on the runway. On the other hand, diversity of planes as an influential factor in designing networks has been overlooked, so far. In the final proposed model besides tackling this deficiency, we have determined procedure of allocating each kind of planes to each runway. A computational result on the US domestic air traortation network in 2004 peak hour demonstrates that the proposed models in this study can ensure a more balanced workload among hubs. Also, former studies in the field of hub location problem have concentrated on some criteria such as flow costs and network construction costs. There are wide gaps in this field where the main challenges of human’s real live cannot be modeled. Delays, environmental damages (such as air pollution), and energy are of important challenges in air traortation industry. Considering the abovementioned criteria, we have proposed a new multi-objective model based on three economic, environmental and energy criteria to solve the capacitated Multiple Allocation hub location problem. A computational result on the US domestic air traortation network is presented.
