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Transcript of Improving Revenue by System Integration and Cooperative Optimization Reservations & Yield Management...
Improving Revenue bySystem Integration andCooperative Optimization
Reservations & Yield Management Study Group
Annual Meeting Berlin 16 - 19 April 2002
UNIVERSITY of PADERBORNUNIVERSITY of PADERBORN
Georg Kliewer Sven Grothklags
Klaus Weber
19.04.2002Slide 2
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Motivation - Planning Processes
FleetAssignment
AircraftRotation
CrewPairing
CrewRostering
OperationControl
NetworkDesign
MarketModeling
RevenueManagement
19.04.2002Slide 3
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Agenda
Business Process
Mathematical Model
Optimisation Algorithm
Fleet Assignment Problem
O&D Revenue Management
Current System Integration
System Integration Approaches
Conclusions
19.04.2002Slide 4
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Fleet Assignment - Business Process
Find most Profitable Subfleet Assignment Use a Subfleet that is Feasible for each Leg Use the Existing Fleet and no extra Aircraft Obey Blocktime and Groundtime Constraints
SchedulingActivity
NetLineApplication
Fleet Assignment
weekly fully-dated
NetLine/Plan
NetLine/Sched
NetLine/Ops
OperationsControl
Development
19.04.2002Slide 5
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Fleet Assignment - Business Process (cont)
19.04.2002Slide 6
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Strategic Profitability Evaluation Model
Strategic-PEM is a forecasting model that measures the network profitability contribution of each schedule scenario
The Strategic PEM forecasts are developed on an O&D basis for a representative week for a schedule period
Input Data: average revenue for the O&Ds market demand for the O&Ds cost model fleeted schedule
Output Data: overall schedule profitability profit information for each leg-subfleet combination
19.04.2002Slide 7
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Strategic Profitability Evaluation Model (cont)
Fleet AssignmentProfitability Evaluation Model
objective function for fleet assignment
assignment
SimulatedAnnealing
Market Share Model
Connection Builder
Spill & Recapture
Revenue & CostEstimation
constrained passenger flow
prelim. capacity assignment
scheduleav. revenues
market demand
itineraries
unconstrained demand
19.04.2002Slide 8
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Fleet Assignment - Mathematical Model
PAD
MUC
FRA
ground arc (v-,v)
xl,f
yv,v+
v v+v-
flight event
leg l xl,f=1 leg l is assigned to subfleet f
yv,v+: aircraft flow on the ground
19.04.2002Slide 9
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Fleet Assignment - Optimisation Algorithm
Fleet Assignment
fleetschedule
restrictions
Accept/Reject
GenerateNeighbor Solution
UpdateSolution
finalassignment
SimulatedAnnealing
Objective Function
Profitability Evaluation Model
19.04.2002Slide 10
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Fleet Assignment - Optimisation Algorithm
S = initial solutionT = warming_updo
do
Snew = neighbor solution (S)
cost = cost(Snew) - cost(S)
if (cost < 0 or accept(cost,T) )
S = Snew
until equilibrium
T = update(T)
until frozen
Heuristic solution method based on local search
1
Frozen
P
Equilibrium
19.04.2002Slide 11
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Fleet Assignment - Results
0,01
0,1
1
10
100
1000
10000
100000
116x2 3337x4 4558x8 4477x9 4452x11 17387x10
problem size (legs x subfleets)
Tim
e (
se
c)
Hill-Climber Simulated Annealing Mixed-Integer Program
Algorithm Hill-Climber Simulated Annealing
Mixed-Integer
Program
-solution quality 98,5% 99,7% >99,9%
19.04.2002Slide 12
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Agenda
Business Process
System Overview
O&D Control Parameters
Fleet Assignment Problem
O&D Revenue Management
Current System Integration
System Integration Approaches
Conclusions
19.04.2002Slide 13
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
O&D Revenue Management – Business Process
Application
NetLine/Plan
NetLine/Sched
NetLine/Ops
NetLine/Price
ProfitLine
BusinessActivities
OperationsControl
Pricing
Revenue Management
Development
19.04.2002Slide 14
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
O&D Revenue Management – System Overview
O&D Forecast Engine
O&D Optimiser
ForecastInterface DB
OptimiserInterface DB
Inve
ntor
y
GDS
GDS
GDS
GDS...
Forecast Building
Demand Forecasts
ControlParameters
O&D Optimiser
ForecastInterface DB
OptimiserInterface DB
Inve
nto
ry
GDS
GDS
GDS
GDS
...
Market Shares
Demand Forecasts
ControlParameters
Market Size Forecast
Price Elasticity Model
Market Size
Bookingswith Fare
InformationFareBuckets
Forecasts based oneither booking histories
or market model and
price elasticity model
or both
e.g. ODIF POSbooking limits
e.g. fare buckets
19.04.2002Slide 15
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
O&D Revenue Management – O&D Control Parameters
EMSR varieties
booking class limits per leg / compartment
on various granularity levels, e.g. ODIF POS
bid prices derived from EMSR curve or approximation
fare bucket limits per leg / compartment
revenue bucket limits per leg / compartment
Dynamic programming
bid prices per leg / compartment
booking class limits derived from bid prices
Parameters to beused by fleetassignment process
Reflect demand demand variability estimated fares
Œ
O&D control parameters depend on type of optimizer
19.04.2002Slide 16
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Agenda
Cooperative Approach
Fleet Assignment Problem
O&D Revenue Management
Current System Integration
System Integration Approaches
Conclusions
19.04.2002Slide 17
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Current System Integration - Cooperative Approach
Profitability Evaluation Model
Market Share Model
Connection Builder
Spill & Recapture
Revenue & CostEstimation
constrained passenger flow
capacity assignment
itineraries
unconstrained demand
Fleet Assignment
Accept/Reject
Fleet Changeon a Leg Sequence
UpdateSolution
1
2
3 SimulatedAnnealing
FinalAssignment
Objective Function
4
5
6
19.04.2002Slide 18
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Current System Integration - Cooperative Approach (cont)
Strategic PEM + Fleet Assignment NetLine/Plan
Tactical PEM + Fleet Assignment NetLine/Sched fully-dated schedule
Basic O&D Fleet Assignment
Approximative revenue estimation
Fast evaluation loop: essential for Simulated Annealing
even faster with internal feedback by passenger flow model
State
19.04.2002Slide 19
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Agenda
Internal Feedback
External Feedback by O&D Revenue Management System
System View
Fleet Assignment Problem
O&D Revenue Management
Current System Integration
System Integration Approaches
Conclusions
19.04.2002Slide 20
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
System Integration – Internal Feedback
Fleet AssignmentProfitability Evaluation Model
Accept/Reject
Passenger FlowLP-Model
Dual Variablesfor Legs
Fleet Changeon a Leg Sequence
UpdateSolution
FinalAssignment
1
2
3
SimulatedAnnealing
Market Share Model
Connection Builder
Spill & Recapture
Revenue & CostEstimation
passenger flow
capacity assignment
itineraries
unconstrained demand
Objective Function
4
5
19.04.2002Slide 21
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Profitability Evaluation Model
System Integration – External Feedback by O&D RMS
Fleet Assignment
Accept/Reject
Fleet Changeon a Leg
Sequence
UpdateSolution
SimulatedAnnealing
FinalAssignment
O&D Revenue Management
O&DForecast Engine
O&D Optimiser
O&D Forecasts
O&D Control Parameters
RevenueEstimation
Objective Function
Capacity Assignment
Market Share Model
Connection Builder
Spill & Recapture
CostEstimation
passenger flow
capacity assignment
itineraries
unconstrained demand
19.04.2002Slide 22
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
System Integration – System Details
1000 950 850 700 670 650 550 510 430 400
1: FRA-TXL, A2: JFK-FRA-TXL, A
3: FRA-TXL, B4: GRU-FRA-TXL, A
5: GRU-FRA-TXL, B6: JFK-FRA-TXL, B
7: FRA-TXL, C8: GRU-FRA-TXL, C
9: JFK-FRA-TXL, C10: FRA-TXL-SVO, A
ODIF-value
1 2 3 4 5 6 7 8 9 10
AU
-Lev
el
1000 950 850 700 670 650 550 510 430 400
1: FRA-TXL, A2: JFK-FRA-TXL, A
3: FRA-TXL, B4: GRU-FRA-TXL, A
5: GRU-FRA-TXL, B6: JFK-FRA-TXL, B
7: FRA-TXL, C8: GRU-FRA-TXL, C
9: JFK-FRA-TXL, C10: FRA-TXL-SVO, A
ODIF-value
1 2 3 4 5 6 7 8 9 10
AU
-Lev
el
Iterative Proration (ProBP)
O&D Revenue Management
O&DForecast Engine
O&D Optimiser
O&D Forecasts
Capacity Assignment
JFK
GRU
FRA
TXL
SVO
JFK
GRU
FRA
TXL
SVO
ODIF POS buckets
O&D Control Parameters
19.04.2002Slide 23
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
System Integration – System Details (cont)
1000 950 850 700 670 650 550 510 430 400
1: FRA-TXL, A2: JFK-FRA-TXL, A
3: FRA-TXL, B4: GRU-FRA-TXL, A
5: GRU-FRA-TXL, B6: JFK-FRA-TXL, B
7: FRA-TXL, C8: GRU-FRA-TXL, C
9: JFK-FRA-TXL, C10: FRA-TXL-SVO, A
ODIF-value
1 2 3 4 5 6 7 8 9 10
AU
-Lev
el
1000 950 850 700 670 650 550 510 430 400
1: FRA-TXL, A2: JFK-FRA-TXL, A
3: FRA-TXL, B4: GRU-FRA-TXL, A
5: GRU-FRA-TXL, B6: JFK-FRA-TXL, B
7: FRA-TXL, C8: GRU-FRA-TXL, C
9: JFK-FRA-TXL, C10: FRA-TXL-SVO, A
ODIF-value
1 2 3 4 5 6 7 8 9 10
AU
-Lev
el
O&D Revenue Management
O&DForecast Engine
O&D Optimiser
O&D Forecasts
O&D Control Parameters
RevenueEstimation
Capacity Assignment
Estimated revenue = sum of EMSR values
1000950
850
700670 650
550510
430400
1 2 3 4 5 6 7 8 9 10 Seats
reve
nue
EMSR curve
19.04.2002Slide 24
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
System Integration – System Details (cont)
O&D Revenue Management
O&DForecast Engine
O&D Optimiser
O&D Forecasts
Capacity Assignment
O&D Control Parameters
Dynamic Bid Price (DynBP)models revenue management as multistage decision process
Bid price matrix per compartment
time to departure
vaca
nt s
eats
Rt-1(x) = max[fi + Rt(x-1), Rt(x)] = max [ufi + Rt(x-u)] u{0, 1}
Rt-1(x) = Rt(x)
t t-1
x
x-1Rt-1(x) = fi + Rt(x-1)
19.04.2002Slide 25
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
System Integration – System Details (cont)
C
Increase
..
.
147.3 146.5
149.5
151.8
145.8
148.7
150.8
147.9
150.1
currentoptimizationpoint
Decrease
remainingcapacity
nextoptimizationpoint
C-1
C-2
t t-1 t-2
time to deptarture
Bid price matrix per compartmentO&D Revenue Management
O&DForecast Engine
O&D Optimiser
O&D Forecasts
O&D Control Parameters
RevenueEstimation
Capacity Assignment
Estimated revenue = sum of bid prices
19.04.2002Slide 26
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
System Integration – Discussion
two loop system revenue estimation loop fleet assignment loop significant runtime
differencescoordination of loops
capacity dependency of revenue management optimization
runtime! Approximation?
partly overlapping system functions (market model, OD-Forecast)
redundancy, requires further integration
forecast uncertainty and actual fares taken into account
simple interfaces between fleet assigner and revenue management system
more accurate revenue estimation
State Challenges
19.04.2002Slide 27
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
O&D Revenue Management System
Current System Integration
Fleet Assignment Problem
Agenda
System Integration Approaches
Conclusions
19.04.2002Slide 28
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
applied in Fleet Assignment Systems of ...
Conclusions - Fleet Assignment in Practice
Simulated Annealing-based Fleet Assignment Optimization
substantial part of commercialFleet Assignment tool
Cooperative Approach
Integrated Approaches
prototype
19.04.2002Slide 29
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Conclusions - Summary
Integration of Fleet Assignment and Revenue Management can improve overall revenue
Facets of the fleet assignment problem introduced:business, mathematics, simulated annealing
Substantial part: Profitability Evaluation Model (PEM)
Revenue management system introduced:particularly important for integration: control parameters
Current state of integration: Cooperative Approach with PEM (without integration of RMS) - successfully used by three airlines
System integration prototype:
based on internal passenger flow model (deterministic LP)
based on external link to O&D RMS: EMSR-based, dynamic programming
good
better
almost perfect
19.04.2002Slide 30
Grothklags, Kliewer, Weber: Improving Revenue by System Integration and Co-operative OptimizationAGIFORS Reservations & Yield Management Study Group Annual Meeting 2002
Conclusions - Ongoing Work, Outlook
Ongoing tests of system integration prototype
Market Model used in FA is also used in Pricing
further Integration possible
Integration of the Passenger Flow Model in Fleet Assignment
optimization approach for enhanced O&D Fleet Assignment
Usage in short-term → pre-implementation phase:
booking dependent (demand driven) fleet assignment
Thank you for your attention!Any questions?
UNIVERSITY of PADERBORNUNIVERSITY of PADERBORN [email protected]