Combining Flight Level Allocation with Ground Holdingto Optimize 4D-Deconfliction

Cyril Allignol and Nicolas Barnierallignol@cena.fr

barnier@recherche.enac.fr

DSNA – ENAC

Ninth USA/Europe ATM R&D Seminar 2011Berlin, 15/06/2011

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 1 / 22

Outline

1 Introduction

2 ContextGround Holding in Europe4D-Trajectory Deconfliction

3 Combining Flight Level Allocation with Ground HoldingVariablesConflict DetectionFL Allocation ConstraintsGround Holding Constraints

4 ResultsFL Allocation StageGround Holding Stage

5 Further Works

6 Conclusion

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 2 / 22

Introduction

Introduction

Congested European Sky

Regulation delays mainly due to en-route sector capacities

Structural limits of the sector-based ATC system reached

Optimization of airspace structure and ATFM regulations: SESAR

Two-Stage ATM Optimization

1 Flight Level Allocation

Vertical separation of 2D + time-intersecting flightsGraph Coloring, but minimization of discrepancy to requested FL

2 Ground Holding

Deconfliction by departure time adjustmentGraph Coloring as special case, minimization of delays

Solved by Constraint Programming (CP)

Versatile modelling tool for combinatorial optimization problem

Optimality proof for feasibility stageC. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 3 / 22

Introduction

Introduction

Congested European Sky

Regulation delays mainly due to en-route sector capacities

Structural limits of the sector-based ATC system reached

Optimization of airspace structure and ATFM regulations: SESAR

Two-Stage ATM Optimization

1 Flight Level Allocation

Vertical separation of 2D + time-intersecting flightsGraph Coloring, but minimization of discrepancy to requested FL

2 Ground Holding

Deconfliction by departure time adjustmentGraph Coloring as special case, minimization of delays

Solved by Constraint Programming (CP)

Versatile modelling tool for combinatorial optimization problem

Optimality proof for feasibility stageC. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 3 / 22

Introduction

Introduction

Congested European Sky

Regulation delays mainly due to en-route sector capacities

Structural limits of the sector-based ATC system reached

Optimization of airspace structure and ATFM regulations: SESAR

Two-Stage ATM Optimization

1 Flight Level Allocation

Vertical separation of 2D + time-intersecting flightsGraph Coloring, but minimization of discrepancy to requested FL

2 Ground Holding

Deconfliction by departure time adjustmentGraph Coloring as special case, minimization of delays

Solved by Constraint Programming (CP)

Versatile modelling tool for combinatorial optimization problem

Optimality proof for feasibility stageC. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 3 / 22

Context Ground Holding in Europe

Ground Holding in Europe

Pre-tactical Flow Regulation

Safer than handling the traffic while airborne

Costly for airspace users, network effect

Sector Capacity and Regulation

Air Traffic Control Centres opening schedules: designed by experts,based on previous traffic and demand

Open sectors capacities: hourly entry rate

Regulation on flows crossing overloaded sectors: Computer AssistedSlot Allocation (CASA/ETFMS) at CFMU

Accuracy and Effectiveness of the Model?

Relevance of sector capacity to model controller workload?

Discrepancies between planned schedule and actual openings

CASA: greedy algorithm (optimality, soundness?)

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 4 / 22

Context Ground Holding in Europe

Ground Holding in Europe

Pre-tactical Flow Regulation

Safer than handling the traffic while airborne

Costly for airspace users, network effect

Sector Capacity and Regulation

Air Traffic Control Centres opening schedules: designed by experts,based on previous traffic and demand

Open sectors capacities: hourly entry rate

Regulation on flows crossing overloaded sectors: Computer AssistedSlot Allocation (CASA/ETFMS) at CFMU

Accuracy and Effectiveness of the Model?

Relevance of sector capacity to model controller workload?

Discrepancies between planned schedule and actual openings

CASA: greedy algorithm (optimality, soundness?)

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 4 / 22

Context Ground Holding in Europe

Ground Holding in Europe

Pre-tactical Flow Regulation

Safer than handling the traffic while airborne

Costly for airspace users, network effect

Sector Capacity and Regulation

Air Traffic Control Centres opening schedules: designed by experts,based on previous traffic and demand

Open sectors capacities: hourly entry rate

Regulation on flows crossing overloaded sectors: Computer AssistedSlot Allocation (CASA/ETFMS) at CFMU

Accuracy and Effectiveness of the Model?

Relevance of sector capacity to model controller workload?

Discrepancies between planned schedule and actual openings

CASA: greedy algorithm (optimality, soundness?)

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 4 / 22

Context 4D-Trajectory Deconfliction

4D-Trajectory Deconfliction

4D-Trajectory Planning

“Strategic” deconfliction (EC project Episode 3)

Several opportunities: flight level, rerouting, delay, speed...

Large scale combinatorial optimization problems

Conflict Model

Finest grain (conflicts) vs aggregated model (sector capacity)

Sliding time windows to handle uncertainty

Two-Stage Trajectory Deconfliction

1 Flight Level AllocationDetection in the horizontal planeVertical separation (Graph Coloring) minimizing discrepancy to RFL

2 Ground HoldingDifference of delays (O

(n2)!) constrained outside conflicting intervals

Minimization of delays

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 5 / 22

Context 4D-Trajectory Deconfliction

4D-Trajectory Deconfliction

4D-Trajectory Planning

“Strategic” deconfliction (EC project Episode 3)

Several opportunities: flight level, rerouting, delay, speed...

Large scale combinatorial optimization problems

Conflict Model

Finest grain (conflicts) vs aggregated model (sector capacity)

Sliding time windows to handle uncertainty

Two-Stage Trajectory Deconfliction

1 Flight Level AllocationDetection in the horizontal planeVertical separation (Graph Coloring) minimizing discrepancy to RFL

2 Ground HoldingDifference of delays (O

(n2)!) constrained outside conflicting intervals

Minimization of delays

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 5 / 22

Context 4D-Trajectory Deconfliction

4D-Trajectory Deconfliction

4D-Trajectory Planning

“Strategic” deconfliction (EC project Episode 3)

Several opportunities: flight level, rerouting, delay, speed...

Large scale combinatorial optimization problems

Conflict Model

Finest grain (conflicts) vs aggregated model (sector capacity)

Sliding time windows to handle uncertainty

Two-Stage Trajectory Deconfliction

1 Flight Level AllocationDetection in the horizontal planeVertical separation (Graph Coloring) minimizing discrepancy to RFL

2 Ground HoldingDifference of delays (O

(n2)!) constrained outside conflicting intervals

Minimization of delays

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 5 / 22

Combining Flight Level Allocation with Ground Holding Variables

Conflict Model

Data

Flight plans and airspace data for one day of traffic

Simulation with CATS [Alliot,Durand 97]

Trajectories sampled every 15 s (catch shortest conflicts)

Notation: flight i at point pki at time tki if not delayed

Variables and Constraints

Decision variables: flight level FLi ∈ [RFLi − devmax,RFLi + devmax]and delay δi ∈ [0, δmax] for each flight i

Auxilliary variables: θki = tki + δi dij = δj − δiConstraints: two flights cannot be at two conflicting points of theirtrajectories at the same time

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 6 / 22

Combining Flight Level Allocation with Ground Holding Variables

Conflict Model

Data

Flight plans and airspace data for one day of traffic

Simulation with CATS [Alliot,Durand 97]

Trajectories sampled every 15 s (catch shortest conflicts)

Notation: flight i at point pki at time tki if not delayed

Variables and Constraints

Decision variables: flight level FLi ∈ [RFLi − devmax,RFLi + devmax]and delay δi ∈ [0, δmax] for each flight i

Auxilliary variables: θki = tki + δi dij = δj − δiConstraints: two flights cannot be at two conflicting points of theirtrajectories at the same time

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 6 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Conflict Detection

ijd

0

i

j

−2w 2w

tki ∈ [1000, 1180], t lj ∈ [600, 750]

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 7 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Conflict Detection

ijd

0

i

j

−2w 2w

t1i = 1000

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 7 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Conflict Detection

ijd

0

i

j

−2w 2w

t2i = 1015

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 7 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Conflict Detection

ijd

0

i

j

−2w 2w370 400

t3i = 1030, [t3

j = 630, t5j = 660], dij 6∈ [370, 400]

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 7 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Conflict Detection

ijd

0

i

j

−2w 2w415370

t4i = 1045, [t3

j = 630− t6j = 675], dij 6∈ [370, 415] ⊆ [370, 415]

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 7 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Conflict Detection

ijd

0

i

j

−2w 2w430370

t5i = 1060, [t3

j = 630− t7j = 690], dij 6∈ [370, 430] ⊆ [370, 430]

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 7 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Conflict Detection

ijd

0

i

j

−2w 2w430370

t6i = 1075, [t4

j = 645− t8j = 705], dij 6∈ [370, 430] ⊆ [370, 430]

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 7 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Conflict Detection

ijd

0

i

j

−2w 2w445370 385

t7i = 1090, [t4

j = 645− t8j = 705], dij 6∈ [385, 445] ⊆ [370, 445]

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 7 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Conflict Detection

ijd

0

i

j

−2w 2w370 385 445

t8i = 1105, [t5

j = 660− t9j = 720], dij 6∈ [385, 445] ⊆ [370, 445]

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 7 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Conflict Detection

ijd

0

i

j

−2w 2w370 385 460

t9i = 1120, [t5

j = 660− t10j = 735], dij 6∈ [385, 460] ⊆ [370, 460]

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 7 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Conflict Detection

ijd

0

i

j

−2w 2w370 400 460

t10i = 1135, [t6

j = 675− t10j = 735], dij 6∈ [400, 460] ⊆ [370, 460]

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 7 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Conflict Detection

ijd

0

i

j

−2w 2w370 415 460

t i11 = 1150, [t7j = 690− t10

j = 735], dij 6∈ [415, 460] ⊆ [370, 460]

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 7 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Conflict Detection

ijd

0

i

j

−2w 2w370 415 460430

t i12 = 1165, [t9j = 720− t10

j = 735], dij 6∈ [415, 430] ⊆ [370, 460]

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 7 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Conflict Detection

ijd

0

i

j

−2w 2w370 460

dij = δj − δi 6∈ [370, 460]

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 7 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Multiply-Conflicting Flight Pair

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ij ] ∪ · · · ∪ [lbkij ..ubk

ij ]

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 8 / 22

Combining Flight Level Allocation with Ground Holding Conflict Detection

Flight Conflicting with Many Other

Constraint Graph of High Degree

Highest degree > 650

Large cliques > 150

One single large connected component

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C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 9 / 22

Combining Flight Level Allocation with Ground Holding FL Allocation Constraints

2D+Time Conflicts

For each pair of flights i 6= j

∀k, l , such that dh(pki , p

li ) < 5 NM (horizontal plane only):

θki 6= θlj

tki + δi 6= t lj + δj

dij 6= tki − t lj

Therefore: dij /∈ CHij = [lb1ij ..ub1

ij ] ∪ · · · ∪ [lbmij ..ubm

ij ]

We note: conflictH(i , j) ⇔ [−δmax, δmax] ∩ CHij 6= ∅

Trajectories truncated to their largest possible level part(below RFL− devmax)

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 10 / 22

Combining Flight Level Allocation with Ground Holding FL Allocation Constraints

FL Allocation: Flows Model

Model

Flights sharing the same route and (almost) same RFL aggregatedinto flows Fk

Extension of conflicts to flows:

conflict(Fk ,Fl)⇔ ∃(i , j) ∈ Fk ×Fl s.t. conflictH(i , j)

Constraints: conflict(Fk ,Fl) ⇒ FLk 6= FLl

Cost: costFL =∑i

|RFLi − FLi |

Limits

Few variables, but very dense constraint graph

Does not solve catch-up conflicts

It was abandoned for the single flight model.

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 11 / 22

Combining Flight Level Allocation with Ground Holding FL Allocation Constraints

FL Allocation: Flows Model

Model

Flights sharing the same route and (almost) same RFL aggregatedinto flows Fk

Extension of conflicts to flows:

conflict(Fk ,Fl)⇔ ∃(i , j) ∈ Fk ×Fl s.t. conflictH(i , j)

Constraints: conflict(Fk ,Fl) ⇒ FLk 6= FLl

Cost: costFL =∑i

|RFLi − FLi |

Limits

Few variables, but very dense constraint graph

Does not solve catch-up conflicts

It was abandoned for the single flight model.

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 11 / 22

Combining Flight Level Allocation with Ground Holding FL Allocation Constraints

FL Allocation: Single Flight Model

For each pair of flights i 6= j

conflictH(i , j) ⇔ [−δmax, δmax] ∩ CHij 6= ∅

Constraints: conflictH(i , j) ⇒ FLi 6= FLj

Cost: costFL =∑i

|RFLi − FLi |

Temporal Relaxation

Very dense graph with costly solutions for feasible values of δmax

Most flights won’t be delayed (or by a very small amount)

Detection with dij = 0 ∈ CHij : solutions with low devmax and costFL

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 12 / 22

Combining Flight Level Allocation with Ground Holding FL Allocation Constraints

FL Allocation: Single Flight Model

For each pair of flights i 6= j

conflictH(i , j) ⇔ [−δmax, δmax] ∩ CHij 6= ∅

Constraints: conflictH(i , j) ⇒ FLi 6= FLj

Cost: costFL =∑i

|RFLi − FLi |

Temporal Relaxation

Very dense graph with costly solutions for feasible values of δmax

Most flights won’t be delayed (or by a very small amount)

Detection with dij = 0 ∈ CHij : solutions with low devmax and costFL

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 12 / 22

Combining Flight Level Allocation with Ground Holding Ground Holding Constraints

Ground Holding Conflict Constraints

For each pair of flights i 6= j after FL allocation

∀k, l , such that dh(pki , p

li ) < 5 NM ∧ dv (pk

i , pli ) < 1000 ft:

θki 6= θlj

Therefore: dij /∈ Cij = [lb1ij ..ub1

ij ] ∪ · · · ∪ [lbmij ..ubm

ij ]

Cost: costmaxGH = max

iδi

costsumGH =

∑i

δi

NP-hard problem

Non European Flights

Flights originating outside the ECAC zone cannot be delayed byEurocontrol instances (≈ 10%): δi = 0

Conflicts between two such flights discarded (a few dozens)

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 13 / 22

Combining Flight Level Allocation with Ground Holding Ground Holding Constraints

Ground Holding Conflict Constraints

For each pair of flights i 6= j after FL allocation

∀k, l , such that dh(pki , p

li ) < 5 NM ∧ dv (pk

i , pli ) < 1000 ft:

θki 6= θlj

Therefore: dij /∈ Cij = [lb1ij ..ub1

ij ] ∪ · · · ∪ [lbmij ..ubm

ij ]

Cost: costmaxGH = max

iδi

costsumGH =

∑i

δi

NP-hard problem

Non European Flights

Flights originating outside the ECAC zone cannot be delayed byEurocontrol instances (≈ 10%): δi = 0

Conflicts between two such flights discarded (a few dozens)

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 13 / 22

Results

Results

Instance Figures

Traffic within French airspace in 2008 (time step: 1 min)

Demand up to 8 700 flights

Up to 37 000 intersecting flights during FL allocation

Up to 315 000 during ground holding

Resolution

All instances solved down to FL0 (except TMA)

Max optimality proof for most of them

A few seconds for FL allocation and about 1 min for ground holding

No optimization of the mean/sum but minimizing search heuristic

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 14 / 22

Results

Results

Instance Figures

Traffic within French airspace in 2008 (time step: 1 min)

Demand up to 8 700 flights

Up to 37 000 intersecting flights during FL allocation

Up to 315 000 during ground holding

Resolution

All instances solved down to FL0 (except TMA)

Max optimality proof for most of them

A few seconds for FL allocation and about 1 min for ground holding

No optimization of the mean/sum but minimizing search heuristic

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 14 / 22

Results FL Allocation Stage

Reduction of the Number of Conflicts After FL Allocation

0

500

1000

1500

2000

2500

3000

3500

4000

0812 0813 0814 1006 1007 1008 1010

RFLAFL

Cannot take climb/descent phase into account (≈ 75% of all conflicts)

All cruising phase conflicts solved for devmax = FL30

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 15 / 22

Results FL Allocation Stage

Distribution of Discrepancies from RFL After Allocation

0

2000

4000

6000

8000

10000

0812 0813 0814 1006 1007 1008 1010

0 10 20 30

0

2000

4000

6000

8000

10000

0812 0813 0814 1006 1007 1008 1010

0 10 20 30

Flows Model Single Flight Model

Cost with Single Flight Model 55% better than with Flows Model

All instances solved with devmax = FL30, costFL = 16 000− 20 000

80% at their RFL, 20% at FL10, 1% at FL20 and a couple at FL30

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 16 / 22

Results Ground Holding Stage

Optimal Max Cost Before and After FL Allocation

0

20

40

60

80

100

0812 0813 0814 1006 1007 1008 1010

RFLAFL

Reduction up to 40% (average 25%)

But max criterion does not reflect the overall amount of delay

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 17 / 22

Results Ground Holding Stage

Sum of delays before and after FL allocation

0

2000

4000

6000

8000

10000

12000

14000

16000

0812 0813 0814 1006 1007 1008 1010

RFLAFL

Reduced by 25% on average (up to 36%)

More consistent than max delay

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 18 / 22

Results Ground Holding Stage

Percentage of delayed flights before and after FL allocation

0

10

20

30

40

50

0812 0813 0814 1006 1007 1008 1010

RFLAFL

Reduced by 5% on average (up to 8%)

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 19 / 22

Further Works

Further Works

More Realistic Modelling

Temporal uncertainties taken into account in real time withiterative resolution over a sliding time window

Side constraints: aircraft rotation (easy to implement but lack ofdata)...

Handling remaining conflicts with CATS resolution modules [Granger,Durand, Alliot 2001] (horizontal manœuvres, speed adjustment)

European Instances

Up to 30 000 flights a day

More RAM or other search paradigms (LS, meta-heuristics,combination with CP)

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 20 / 22

Further Works

Further Works

More Realistic Modelling

Temporal uncertainties taken into account in real time withiterative resolution over a sliding time window

Side constraints: aircraft rotation (easy to implement but lack ofdata)...

Handling remaining conflicts with CATS resolution modules [Granger,Durand, Alliot 2001] (horizontal manœuvres, speed adjustment)

European Instances

Up to 30 000 flights a day

More RAM or other search paradigms (LS, meta-heuristics,combination with CP)

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 20 / 22

Further Works

Handling Uncertainties with Sliding Time Window

T3

4T

Tw

2σ

3σ

initT

2T

t = 0

t =

t =

t =

1Tσ

uncertainty on take−off time

frozen zone

modifiable zone

σ

Flights with departure time between t − σ and t are “noised”

If the uncertainty brings them back to the “modifiable zone”, they aretaken into account again for allocation

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 21 / 22

Conclusion

Conclusion

ATM

Flight level allocation and ground holding combined

Deconfliction vs aggregated regulation

FL allocation with very low discrepancies to RFL

Amount of allocated delay compatible with typical CFMU figures

Large problem but optimality proof (w.r.t. max) obtained with CP

Has to be combined with other strategies (e.g. sliding windows)when managing uncertainties

CP

Versatile technology: quick prototyping, various search strategies,incremental refinement of the model, side constraints...

CP technology scalable to such LSCOP, even with ECAC instances?

May be combined with other search paradigms: LS to solve CSP, CPto speed up LS...

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 22 / 22

Conclusion

Conclusion

ATM

Flight level allocation and ground holding combined

Deconfliction vs aggregated regulation

FL allocation with very low discrepancies to RFL

Amount of allocated delay compatible with typical CFMU figures

Large problem but optimality proof (w.r.t. max) obtained with CP

Has to be combined with other strategies (e.g. sliding windows)when managing uncertainties

CP

Versatile technology: quick prototyping, various search strategies,incremental refinement of the model, side constraints...

CP technology scalable to such LSCOP, even with ECAC instances?

May be combined with other search paradigms: LS to solve CSP, CPto speed up LS...

C. Allignol, N. Barnier (DSNA – ENAC) 4D-Deconfliction ATM 2011 22 / 22