## References

### Mukherjee, A., D. J. Lovell, M. O. Ball, A. R. Odoni, and G. Zerbib. (2005)

. “Modeling Delays and

Cancellation Probabilities to Support Strategic Simulations.” Proceedings of the 6th USA/Europe Air Traffic Management R&D Symposium, Baltimore, MD.
Mukherjee, A., D. J. Lovell, M. O. Ball, A.M. Churchill, and A. R. Odoni. (2007). “Using Optimization and Queuing Models to Estimate Long

- Term Average Flight Delays and Cancellation Rates.” Proceedings of the Sixth Triennial Symposium on Transportation Analysis, Phuket, Thailand.**Number of Ops Sample Days**  **Av erage A**  **rrival Delay**  **Fraction flights**

**cancelled**

1030 46 8.3 1.3% 1090 45 11.9 1.6% 1130 28 17.9 2.1% 1180 38 20.1 2.5% 1230 28 23.2 2.7% 1240 27 24.8 3.7% 1270 21 26.8 4.5% 1360 * 33.2 4.7% 1430 * 42.8 6.1%

* MIT queuing model; UMD network flow cancellation prediction modelNotes

Drawn from 10-2001-1/2002 Drawn from 9/2002-12/2002 Drawn from 6/2003-8/2003 Drawn from 3/2004-4/2004 Drawn from 3/2006-4/2006 Drawn from 7/2004-8/2004 Drawn from 6/2000-8/2000 Demand: 110%*8/2/2007, Capacity : all of 2004 Demand: 115%*8/2/2007, Capacity : all of 2004

**use this one-->**

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0

0 200 400 600**E x** **p e** **c t** **e d** **D e** **l a** **y p** **e r** **O p** **e r** **a t** **i o** **n (** **M i** **n )**  

### EWR Delay **M odel** 

6.0% 7.0% 8.0%**E x** **p e** **c t** **e d** **C a** **n c** **e l** **l a** **t i** **o n** **s (** **P c** **t )**  

### EWR Cancellation Model**use this one-->**

0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0%

0 200 400 600**E x** **p e** **c t** **e d** **C a** **n c** **e l** **l a** **t i** **o n** **s (** **P c** **t )** 0.000281 y = 0.0822x

- 76.865 R2 = 0.9846

800 1000 1200 1400 1600 **Daily Operations**  

### EWR Delay

**M odel** 

y = 0.0002e 0.0039x R2 = 0.9432 

### EWR Cancellation Modely = 0.0001x

- 0.1158 R2 = 0.9374

800 1000 1200 1400 1600 **Daily Operations** **Number of Ops Sample Days**  **Av erage A**  **rrival Delay**  **Fraction flights**

**cancelled** 660 159 11.6 0.9% 760 296 13.1 1.1% 880 93 16.4 1.4% 970 95 21.5 1.3% 1110 86 22.1 1.6% 1230 89 23.6 2.4% 1290 42 31.2 4.3% 1420 * 47.8 6.1%

* MIT queuing model; UMD network flow cancellation prediction model

**use this one-->**

**use this one-->** 0.0 10.0 20.0 30.0 40.0 50.0 60.0**E x** **p e** **c t** **e d** **D e** **l a** **y p** **e r** **O p** **e r** **a t** **i o** **n (** **M i** **n )** 

4.0% 5.0% 6.0% 7.0%**E x** **p e** **c t** **e d** **C a** **n c** **e l** **l a** **t i** **o n** **s (** **P C** **T )** 0.0% 1.0% 2.0% 3.0%**E x** **p e** **c t** **e d** **C a** **n c** **e l** **l a** **t i** **o n** **s (** **P C** **T )** Notes

Drawn from 9/2001-5/2002 Drawn from 6/2002-3/2003 Drawn from 6/2004-9/2004 Drawn from 6/2005-9/2005 Drawn from 8/2006-11/2006 Drawn from 5/2007-9/2007 Drawn from 5/2007-9/2007 Demand: 110%*8/2/2007, Capacity : all of 2006

y = 3.7866e 0.0017x R2 = 0.9317

0.0 10.0 20.0 30.0 40.0 50.0 60.0

0 200 400 600 800 1000 1200 1400 1600 **Daily Operations**  

### JFK Delay

**Model**

y = 0.0016e 0.0024x R2 = 0.8739 4.0% 5.0% 6.0% 7.0% 

### JFK Cancellation Model0.0% 1.0% 2.0% 3.0%

0 200 400 600 800 1000 1200 1400 1600 **Daily Operations** <---only actual observationsOperations #ofday s average_delay

1110 125 12.5 1160 65 14.9 1220 85 16.6 1300 28 24.0 1350 38 35.7 1400 * 47.8

* MIT queuing model

12.51799001 14.88211263

16.6390643 23.95697482 35.67300157

47.8 delay m inutes per operation = 0.07e 0.0046daily ops

R 2 = 0.9605

0 10 20 30 40 50 60

1000 1100 1200 1300 1400**A v** **e r** **a g** **e A** **r r** **i v** **a l** **D e** **l a** **y (** **m i** **n u** **t e** **s )** 

**Operations**



### UMD Delay

**Simulation Runs for LGA**Note: at some very low pct cancels, there no costs of cancellation because all or most passengers are reaccommodated. But, at very high levels, passengers are not reaccommodated. The conservative approach is to assume the costs of cancellation at least = delay costs

scheduled ops expected delay s at

sched ops cancels expected actual ops net of cancels

1150 13.9 5.0% 1093 1175 15.6 5.4% 1111 1200 17.5 5.9% 1129 1225 19.6 6.4% 1146 1250 22.0 7.0% 1162 1275 24.7 7.6% 1178 1300 27.7 8.3% 1192 1325 31.1 9.0% 1205 1350 34.8 9.8% 1217 1375 39.1 10.7% 1228 1400 43.8 11.7% 1237

1500expected delay s

at expected actual ops

13.9

11.6 12.6 13.6 14.7 15.8 16.8 17.9 18.9 19.9 20.7Operations #ofday s Cancellation_probability

1110 125 0.048 1160 65 0.044 1220 85 0.068 1300 28 0.073 1350 38 0.092 1400 * 0.13 * UMD network flow cancellation prediction model

Prob. of cancellation = 0.001e 0.0034 operations R 2 = 0.9088

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

1000 1100 1200 1300 1400**C a** **n c** **e l** **l a** **t i** **o n** **P r** **o b** **a b** **i l** **i t** **y**

**Operations**1500