1 Flexible Airlane Generation to Maximize Flow Under Hard and Soft Constraints Shang Yang, Joseph S. B. Mitchell, Stony Brook University, Stony Brook, NY 11794 Jimmy Krozel, Metron Aviation, 45300 Catalina Court, Dulles, VA 20166 Valentin Polishchuk, Helsinki Institute for Information Technology, Helsinki, FI-00014 Joondong Kim, and Jingyu Zou Stony Brook University, Stony Brook, NY 11794 ABSTRACT We consider a multicriteria optimization problem of simultaneously routing several classes of aircraft through an airspace at a fixed flight level in the presence of various types of constraints. Hard constraints are formed by hazards through which no aircraft can safely fly (e.g., severe convection, turbulence, or icing). Soft constraints are formed by hazards through which some pilots or airlines decide to fly while others do not (e.g., moderate turbulence or icing). We compute flight paths for two aircraft classes: Class-1 aircraft avoid hard constraints but are willing to fly through soft constraints, and Class-2 aircraft avoid both hard and soft constraints. Our work assists in the design of future operational concepts in which jetway routing is retired and aircraft paths are allowed to adjust to the shapes and positions of constraints. We are interested in determining the capacity of an airspace and feasible routes across an airspace with hard and soft constraints, given as input the demand profile indicating how many Class-1 and Class-2 aircraft are scheduled to enter the airspace. We report on experiments both with real and with synthesized weather data.