ANALYSIS FRAMEWORK FOR OPERATIONAL EFFECTS OF DIFFERENT CONGESTION MANAGEMENT MEASURES AT CLUSTERED AIRPORTS Loan T. Le Research Sponsors: NASA ARC, FAA 1 st International Conference on Research in Air Transportation - ICRAT 2004, November , Zilina, Slovakia

Newark Kennedy LaGuardia White Plains Islip 30.7 miles 46 miles 12.5 miles TEB New York City Airports

Newark Kennedy White Plains Islip TEB LaGuardia Slot controlled

Delta’s capacity distribution

Research problem Operational and economic implications Which congestion measures efficiently balance network load and maintain competition? How the airlines distribute capacity among clustered airports? What are the economic factors that effect their decisions?

Research problem - Limited #IFR slots during specific time periods - Negotiation-based allocation 1968 High-Density-Rule at LGA, JFK, DCA, ORD Exempted from HDR at LGA certain flights to address competition and small market access AIR Cap of the #exemption slots Lottery at LGA 1978 Deregulation Use-it-or- lose-it rule based on 80% usage 1985 Slot ownership 2007 End of HDR. What’s next? -Congestion pricing? -Slot Auction? -Administrative?  Provisions for future slot allocation schemes  Find airline cost-effective competitive equilibrium Removal of HDR at ORD

Air Transport is an Economic System Behavior individual’s algorithm for participation Environment rights, costs, values, technology, constraints Institution publicly implemented algorithm for goods allocation property rights, constraints reallocations personal information & system constraints rules and procedure messages investments Network carrierLow-cost carrierNew entrants Congestion pricing Auction Hub, international airport Non-hub domestic airport Foreign carriers Administrative

Scheduling process (Barnhart) Schedule Planning Route Development Schedule Development o Frequency Planning o Timetable Development o Fleet Assignment o Aircraft Rotations Crew Scheduling Airport Resource Management Pricing Revenue Management Sales and Distribution Operations Control SHORT TERM LONG TERM TACTICAL STRATEGIC Time Horizon Types of Decision Fleet Planning

Slot valuation model -Fixed fleeted schedule -Estimated unconstrained demand Estimated Profit ?

Slot valuation model Y X Z 50 seats $ seats $110 D XY =40 D YZ =30 $200 D XZ =30 Supply Demand Assignment Cost = Operating Cost + Spill Cost Estimated Profit = Estimated revenue – Assignment Cost A Passenger Mix problem -Fixed fleeted schedule -Estimated unconstrained demand Estimated Profit

Slot valuation model Y X Z D XY D YZ D XZ Early Morning Schedule Demand Assignment Cost = Operating Cost + (Spill Cost – Recapture Revenue) Y X Z D ’ XY D ’ YZ D ’ XZ Late Morning Schedule Demand recapture

Slot valuation model Demand spilled from p to r with successful rate b p r Initial Spill Recapture Excess demand A Passenger Mix model: Total Spill Unconstrained demand

Fleet Assignment Problem network nodes Objective: Find the most cost-effective fleeting Constraints: - Fleet Availability - Network balance

Fleet Assignment Problem each flight is assigned one fleet f k,i =1 if fleet k is assigned to flight i in-flow = out-flow fleet availability

Integrated Model (Lohatepanont) Fixed schedule FAM PMM

Airline-specific strategies Decision variables: f k,i  Profit-oriented:  Operationally-constrained:  Flexibility  Frequency-oriented:

Summary and future work Summary:  role of network balancing in addition to local optimization  increasing interest in agent-based modeling and simulation Future work:  Analysis to major airlines operating at the 5 airports  Gaming and competitive behavior  Airline-specific modeling  Control for environmental effects (season)