This paper presents a Mixed Integer Programming model for optimal airspace sector design based on basic volume aggregation, focusing on workload balance and air traffic flow convexity. To overcome potential computational limitations, we develop a simple two-stage heuristic approach. The heuristic approach are evaluated using real-world traffic data from the Madrid Area Control Center, with the MIP as a benchmark. Our key contributions include: (1) the first rigorous mathematical formulation for this problem, (2) a fast heuristic achieving near-optimal solutions in under one second, and (3) a comprehensive assessment across various traffic scenarios. Results show that our MIP model generates operationally relevant sector designs, and the heuristic could provide good-quality solutions with exceptional efficiency. This research advances airspace management techniques, offering both theoretical insights and practical tools for optimizing air traffic control.