The Europe-Asia-Oceania air route is experiencing rapid growth, traditionally served by direct legacy flights but increasingly dominated by hub-based carriers. These airlines leverage large, single-hub models to capture transfer traffic. However, limited research exists on how to efficiently design and operate multi-hub networks for international connectivity. Existing models either oversimplify hub capacities or focus solely on fleet planning and re-timing, lacking an integrated, schedule-based approach. This research develops an integrated decision support model that combines a capacitated multi-allocation p-hub location problem with airline schedule design under operational constraints and competitive dynamics. A multi-step iterative method connects hub assignment and scheduling using a genetic algorithm to ensure feasibility, connectivity, and profitability. The findings reveal that adding hubs initially boosts network efficiency and profitability, though marginal benefits diminish after a certain number of hubs. The integrated model significantly narrows the gap between theoretical and actualized profitability, showing a 7.6\% increase in daily profit for the scheduling model over iterations. This research offers a crucial decision-support tool for long-term airline network planning, particularly in rapidly expanding aviation markets. Its ability to jointly optimize hub locations and flight schedules under operational constraints provides substantial utility for diverse airline network planning scenarios, leading to more viable and profitable network configurations.