Configuring Airspace Sectors with Approximate Dynamic Programming

In response to changing traffic and staffing condi-tions, supervisors dynamically configure airspace sectors by assigning them to control positions. A finite horizon airspace sector configuration prob-lem models this supervisor decision. The prob-lem is to select an airspace configuration at each time step while considering a workload cost, a re-configuration cost, and a constraint on the num-ber of control positions at each time step. Three algorithms for this problem are proposed and evaluated: a myopic heuristic, an exact dynamic programming algorithm, and a rollouts approxi-mate dynamic programming algorithm. On prob-lem instances from current operations with onl