ANALYSIS FRAMEWORK FOR OPERATIONAL EFFECTS OF DIFFERENT CONGESTION MANAGEMENT MEASURES AT CLUSTERED AIRPORTS Loan T. Le Research Sponsors: NASA ARC, FAA.

ANALYSIS FRAMEWORK FOR OPERATIONAL EFFECTS OF DIFFERENT

CONGESTION MANAGEMENT MEASURES AT CLUSTERED AIRPORTS

Loan T. Le

Research Sponsors: NASA ARC, FAA

1st International Conference on Research in Air Transportation - ICRAT 2004, November 22-24 2004, Zilina, Slovakia

Newark

Kennedy

LaGuardia

WhitePlains

Islip

30.7 miles

46 miles

12.5 miles

12.5 miles

12.5 milesTEB

New York City Airports

Newark

Kennedy

WhitePlains

Islip

TEB

LaGuardia

Slot controlled

Slot controlled

Delta’s capacity distribution

0

2000

4000

6000

8000

10000

Jan-00 Jun-00 Nov-00 Apr-01 Sep-01 Feb-02 Jul-02 Dec-02 May-03 Oct-03 Mar-04 Aug-04

Month

Delta Airlines Monthly Operations at LGA

LaGuardia Newark Kennedy

Frequency Changes Compared to Jan 2000

-60

-40

-20

0

20

40

%

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 atLGA, JFK, DCA, ORD

4.2000

Exempted from HDR at LGA certain flights

to address competition

and small market access

AIR-211.2001

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

6.2003

Removal of HDR at ORD

Air Transport is an Economic System

Behaviorindividual’s algorithm

for participation

Environmentrights, costs, values,

technology, constraints

Institutionpublicly implemented algorithm for goods

allocationproperty rights, constraints

reallocations

personal information & system constraints

rules and procedure

messagesinvestments

Network carrier Low-cost carrier New 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

SH

OR

T T

ER

M

LO

NG

TE

RM

TA

CT

ICA

L

ST

RA

TE

GIC

Tim

e H

oriz

on

Types of D

ecision

Fleet Planning

Slot valuation model

-Fixed fleeted schedule-Estimated unconstrained demand

Estimated Profit

?

Slot valuation model

Y

X

Z

50 seats $140

50 seats $110

DXY=40

DYZ=30

$200

DXZ=30

Supply

Demand

Assignment Cost = Operating Cost + Spill CostEstimated Profit = Estimated revenue – Assignment Cost

A Passenger Mix problem

-Fixed fleeted schedule-Estimated unconstrained demand

Estimated Profit

Slot valuation model

Y

X

Z

DXY

DYZDXZ

Early MorningSchedule

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 bpr

Initial Spill Recapture

Excess demand

A Passenger Mix model:

Total Spill Unconstrained demand

Fleet Assignment Problem

network nodes

Objective: Find the most cost-effective fleetingConstraints:

- Fleet Availability- Network balance

Fleet Assignment Problem

each flight is assigned one fleet

fk,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: fk,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)