GroundStar Users Conference 2012 : Madrid

1. Optimization: Back to the Core
7Th GroundStar User´s Conference
7Th GroundStar User´s Conference
Madrid, 12-14 of September 2012

2. Optimization: Back to the Core
7Th GroundStar User´s Conference
1. Reasons and motivation of the optimization
2. Necessity, characterization, priorities
3. Functional design of the optimization algorithm
4. Example of an optimization model : Pax Dep.
5. Lesson learnt in the IB´s optimization process
6. Future lines of development of the optimization
Index
Pag : 2

3. Why back ?, something has been forgotten?
Optimization: Back to the Core
7Th GroundStar User´s Conference
• In many projects it´s raised a common perception
about the optimization failure
• The perception about the pending lesson
persuades all the actors to not admit the state of the
implementation
• A rejection from the final users is always a present
risk not properly managed
• The expected improvement in terms of FTE for all
dispatching duties finally does not satisfy the
original Business Plan
Pag : 3

4. Optimization: Back to the Core
7Th GroundStar User´s Conference
Why core ?, It´s really so important the optimizer ?
• Nobody doubts that Google´s heart it´s
represented by its optimizer.
• The core aims of any digital support within the
airport operational framework are :
• Velocity
• Effectiveness
• Comprehensive analysis
• Reduced men hours requirements
• Traceability
• Standardization of decisions
• Those attributes have the possibility to be
achieved just with de present of a strong
optimization component.
Pag : 4

5. Optimization: Back to the Core
7Th GroundStar User´s Conference
Which are the failure reasons of the optimization processes ?
Optimization Iceberg
Functional Model
Wrong
Qualification profile
Functional Model
Absence of Priorities
Poor realism of the
physical model
Employee
acceptance
Optimize requires to extract in
advance the business reason hidden
over a daily human interaction
We mainly focus the problem on the
employee acceptance
To design the airport trying to
reproduce as much as possible all the
particularities many times is the
easiest and faster 1st approach
All the skipped steps during the
configuration staged before or later
appear as constraints to the best
optimization
Conceptualization
and
development
phase
Implementation
Pag : 5

6. % representation
%
weight
Optimization: Back to the Core
7Th GroundStar User´s Conference
Do we really know what it´s needed to be optimized ?
• Despite It´s seems to be really obvious, first stage just requires to clearly identify which are the key
factors we want to potentiate automatically with the optimization. All of them would have to be weighted for
immobile and mobile resources
Mobile resources optimization Inmmobile resources optimization
% representation
%
weight
Tasks
Emp
Rotation
Travel
Time
Time
Based
Team
Based
Travel
Time
Time
Based
Team
Based
% representation
%
weight
% representation
%
weight
Fuel
Balanc.
Usage
Travel
Time
Time
Based
Tasks
Travel
Time
Time
Based
Tasks
Pag : 6

7. Optimization: Back to the Core
7Th GroundStar User´s Conference
A global understanding of the business requirements are needed in order to unlock
the optimization problem from its firt stage
Passenger Department
 Check-in & Boarding Tasks
 Cross utilized
 Shared between airlines
Baggage Area
 Departure & Arrival Baggage
 Cross utilized between all areas
 Oversize pieces also managed
Load & Unload
 Team based structure
 A car is needed for transport
 Shared between terminals
Key Priorities:
 Boarding & Iberia´s flights
 Wide Bodies preferred
 Peak Hours more important
Key Requirements:
 Qualification Profile
 Training status
 Function status
Hygienic and ergonomic variables
 Rotation of roles between the Staff
 Minimize the Travel Time
 Balanced workload
 Authorized breaks
Key Constraints:
 Ramp & Passenger Network
 Sign In & Sign Out point
 Max. Ramp Speed
Pag : 7

8. Optimization: Back to the Core
7Th GroundStar User´s Conference
Quantity & Quality of the optimization variables
#
Flights/carroulsels
#Baggage
/
Flight
#
Airline
#Lateral
#ULDs:
Local/
Business
#Airline
#ULDs
#
Short
Connections
#PKNs
#aircraft
Type
#
Pax
/
Flight
#Airline
#Boarding
Gate
#
Agents
/
flight
#PMRs/WCHR/UMs
Number
of
passengers
waiting
to
be
board
Number
of
baggage
waiting
to
be
loaded
Number
of
ULDs
waiting
to
be
loaded
Boarding
• Besides the
relevance of the
base variables in
order to track the
evolution of the
execution , it´s
essential to identify
a drop-style metric
linked with each
significance task
type
• For each
operational process
It´s needed to be
identify the best
Taylor-made set of
optimization
variables
ULDs
Baggage
Pag : 8

9. Optimization: Back to the Core
7Th GroundStar User´s Conference
Index
1. Reasons and motivation of the optimization
2. Necessity, characterization, priorities
3. Functional design of the optimization algorithm
4. Example of an optimization model : Pax Dep.
5. Lesson learnt in the IB´s optimization process
6. Future lines of development of the optimization
Pag : 9

10. Optimization: Back to the Core
7Th GroundStar User´s Conference
Which are the variables that affect in the optimization?
Passenger variables
Aircraft type (capacity)
 Number of passengers
Per class
Long/medium/short haul,
Local/transit
Forecast 60/30/3 days & day of operation
 Clients arrival profiles
 Per type of traffic, week day, timeframe
Check-in process time
Service level
Number of check-in counters available
Number of bags
Planification variables
1 of 2
Impredictable variables
•Special services (Missconnections, Ums..)
•Resources absences
•Infraestructure restrictions
•Vehicles availability
Pag : 10
Impredictable variables
Passenger variables
Inmobile resources variables
Business Rules
Resources capabilities
Social Restrictions
Travel Network

11. Optimization: Back to the Core
7Th GroundStar User´s Conference
Which are the variables that affect in the optimization?
Travel Network
•Travel time
•Distances
Business Rules
•Boarding task automaticaly ends when the
agent transmit the total on board to the
coordinator
•Breaks automatically started
•Maximum Overlapping
•Optimization window
Resources capabilities
•Functions & Qualifications
Hierarchy
Incompability
Social Restrictions
•Break buffer restrictions
•Restriction of length of certain type of tasks
(stand up tasks)
•Final shift travel time to log-out location
Optimization variables
2 of 2
Inmobile resources variables
•Inmobile resources assignment
Stand: finger/remote
Virtual stands
Gate (virtual locations)
Baggage carrousel
Airport authority rules
Local belts
•Number of concurrent flights/bags
Pag : 11

12. Optimization: Back to the Core
7Th GroundStar User´s Conference
Strategic Optimization Canvas for each Work Area
Competing factor
Offering
levels
Travel
Time
Overlap Team Capacity
Split.
Rules
Breaks
Sign
In/Out
Location
Competing factor
Offering
levels
Travel
Time
Overlap Team Capacity
Split.
Rules
Breaks
Sign
In/Out
Location
Load & Unload.
Check-In & Boarding
 Each particular Work Area is represented by an
individual profile.
 The unique optimization footprint shows like a
DNA the weighted priorities linked with the partial
behavioral.
 The global optimization behavior is more than the
simple addition of the total sum of the individual
ones.
 Each task individually has the possibility to be
escalated in term of priorization.
 It´s healthy to establish a trial & failure cyclic
approach during the establishment of the final
strategic optimization canvas of each work area.
 Each competing factor is leading the global result
of the optimization for each work area
Pag : 12

13. Optimization: Back to the Core
7Th GroundStar User´s Conference
Optimization Scenarios : The easiest way to react to the real changes
Scenario
Base
Scenario
1
Scenario
2
Scenario
3
Scenario
4
 The more severe is the environment the less complex should the scenario
 The optimization exceptions try to strictly modify the behavior by changing the priorities of each task
 The creation of the Scenarios should be faced like an continuous ongoing issue
Daily Operation
Delays
Low Visibility
Snow Crisis
Accident
Task to be priorized Ergonomic factors & Soft rules
Gradient of severity
Pag : 13

14. Optimization: Back to the Core
7Th GroundStar User´s Conference
Optimization Framework : An evolutionary process
Montly
Weekly
Pre.Plan
Real
Time
Pag : 14
M1 M2 M2
W1 W2 W3 W4 W5 W1 W2 W3 W4 W5 W1 W2 W3 W4 W5
Past
Frozen
Window
Optimization
Timeframe
Future
Real Time

15. Optimization: Back to the Core
7Th GroundStar User´s Conference
Index
1. Reasons and motivation of the optimization
2. Necessity, characterization, priorities
3. Functional design of the optimization algorithm
4. Example of an optimization model : Pax Dep.
5. Lesson learnt in the IB´s optimization process
6. Future lines of development of the optimization
Pag : 15

16. Optimization: Back to the Core
7Th GroundStar User´s Conference
Optimization algorithm parameters
Optimization
Algorithm
Basic Settings
Organization
Business Process
Miscellaneous
Pag : 16

17. Optimization: Back to the Core
7Th GroundStar User´s Conference
Optimization algorithm parameters
Task
duration
Qualifi.
Shift
restrictions
Travel
time
Overlapping
Task
priority
Rotation of
task type
Work
Load
Reduce
Gaps
Restriction
for
the
optimizer
high
low
Business Priority
high
medium
medium
low
Combine, Divide and… Conquer!
Pag : 17

18. Optimization: Back to the Core
7Th GroundStar User´s Conference
Optimization algorithm parameters
This makes that shifts which share common start and end times are
sorted different every day, thus assigning the same orders to
different shifts.
This way, staff doesn't have to do the same orders every day.
RandomShiftOrder = 1
ConsiderMinOrderLength = 1
PlanFullShiftLengthTasks = 1
PreferResourceWithoutTask = 1
Do not plan tasks with length shorter than a predefined value.
Plan full shift length tasks first.
The resources with no planned task are sorted first.
GS Real Time INI file
1 of 2
Pag : 18

19. Optimization: Back to the Core
7Th GroundStar User´s Conference
Optimization algorithm parameters
GS Real Time INI file
With the activation of this parameter, for the algorithm the
Workload is much more important than any other cost parameter.
The optimizer plans the next task always to the resource with the
lowest workload.
Used for Real Time of Turnarround managers, where overlapping
is allowed for certain type of tasks.
SortWorkLoad = 1
Do not plan tasks with length shorter than a predefined value.
This makes that shifts which share common start and end times are
sorted different every day, thus assigning the same orders to
different shifts.
This way, staff doesn't have to do the same orders every day.
AlphaEarlyStart = 1
RandomShiftOrder = 1
2 of 2
Pag : 19

20. Optimization: Back to the Core
7Th GroundStar User´s Conference
Index
1. Reasons and motivation of the optimization
2. Necessity, characterization, priorities
3. Functional design of the optimization algorithm
4. Example of an optimization model : Pax Dep.
5. Lesson learnt in the IB´s optimization process
6. Future lines of development of the optimization
Pag : 20

21. Optimization: Back to the Core
7Th GroundStar User´s Conference
Iberia optimization case. Passenger department.
Flight Schedule
Resiber
PlanControl Rostering RT-Preplanning Real Time Control
Web Roster BI & AOM
Passenger Forecast
•Task assignment
•Sign-in location
•Teaming
•Detection of demand
not covered
Statistics
• Number of Passengers per flight
• Scheduled Operation VS Real Operation
Sign-in Location
•Create NetDemand
•Transfer existing shifts
from Rost. To Plan.
•Create efficient shifts
•Assign shifts to Staff
•Shifts modifications if
needed
•Periodical reviews
Demand VS Supply
Shifts Swaps
•Shifts + Functions +
Special activities
•Automatic Optimized
assignment of tasks to
staff
•Anual FullTimers
shiftpattern
Planning…Preplanning…Real time INFORM Tool
Pre-Season
In-Season
Post Day of Operation
IB Tool
2 of 2
Pag : 21

22. Optimization: Back to the Core
7Th GroundStar User´s Conference
Iberia optimization case. Passenger department.
Planning…Preplanning…Real time
Planning parameters and Planning business
rules are a reflex of the real time ones, to
obtain an optimum result in the resources
availability and assignment.
Same Rules
Same task priorities
Boardings
Check-in
A precise coordination process is followed to update the business rules
simultaneously in the planning department and Real Time Maint. Team.
Pag : 22

23. Optimization: Back to the Core
7Th GroundStar User´s Conference
Iberia optimization case. Passenger department : facts & figures
Shifts per day
Workarea
Check-in + Boarding
Allocators
Qualifications
Employees
Tasks per day in Real Time
70 different log-in locations
Iberia specific + third companies
In 200 different locations
5 different contract types
Check-in and boarding tasks mixed in one shift
Pag : 23

24. Optimization: Back to the Core
7Th GroundStar User´s Conference
Iberia optimization case. Passenger department.
Specific characteristics for the KP optimization
Cross utilization between check-in and boarding areas.
Tasks distributed in 2 buildings separated 2.5 kilometers with 1 security control.
Combination of agents with 3 different level of experience for boardings.
Breaks need to be asigned in a specific shift timeframe.
Limit total minutes of certain tasks in an agent shift, due to “social restrictions”.
Specific third parties tasks that require fix qualifications and procedures.
Certainty that the agent is located in the task location is a must.
Pag : 24

25. Optimization: Back to the Core
7Th GroundStar User´s Conference
Iberia optimization case. Passenger department.
Criteria and model for the KP optimization
End shift travel time
Automatically the agent has
travel time assigned to come
back from the last task location to
the check-in area.
Function&Qualification model
Based on the ambitious targets we stablished for
the Real time system, the F&Q model was carefully
defined…and redefined.
Some adjustments in the operation side were
needed (training…).
“Social”
System
VS
Operation
Standing tasks
The system takes into account
the minutes in a shift that are
dedicated to the tasks types that
involved standing up, so that an
employee does not overpass the
maximum limit.
Pag : 25

26. Optimization: Back to the Core
7Th GroundStar User´s Conference
Iberia optimization case. Passenger department.
Auto sticking
Breaks are automatically stuck to
the previous task when the agent
ends the task in the staff
notification, and the break is
automatically started.
Event related tasks
Boarding task automaticaly ends
when the agent transmit the total
on board to the turnarround
manager.
Criteria and model for the KP optimization
Overlapping
Allowed for tasks with a certain
qualification and for some
minutes.
Productivity
Log-in
In the check-in area, the log-in
point is the first task start
location.
Pag : 26

27. Optimization: Back to the Core
7Th GroundStar User´s Conference
Iberia optimization case. Passenger department.
Pag : 27
Old allocation model before the optimization
Current allocation composition with the optimizer
Compressed view of the optimization window at the Pax.department

28. Optimization: Back to the Core
7Th GroundStar User´s Conference
Iberia optimization case. Passenger department.
Pag : 28
 Number of Unplanned tasks after pre-planning
 Minutes from last task to end shift time report to
measure productivity and shift feasibility.
 Report with the performance of the break
assignment, to assure that they are staggered.
 Rotation of task type performance report.
 On-time start of the task fulfillment.
Optimization evolution metrics

29. Optimization: Back to the Core
7Th GroundStar User´s Conference
Index
1. Reasons and motivation of the optimization
2. Necessity, characterization, priorities
3. Functional design of the optimization algorithm
4. Example of an optimization model : Pax Dep.
5. Lesson learnt in the IB´s optimization process
6. Future lines of development of the optimization
Pag : 29

30. 010111110000111010101110101000100100000110011
Optimization: Back to the Core
7Th GroundStar User´s Conference
Lesson learnt
As in a travel through time machine, all the pieces affect to the complete mechanism
• The way we model the tasks
• The way we define the qualifications
• The way we model the travel network
…
What you define today will have
impact in the results you will obtain in
a long term.
Think beyond the present: since the first step of
the model approach, we are setting the basis of a
complex and solid architecture that will remain
for long time.
Past determines present, past determines future.
Pag : 30

31. Optimization: Back to the Core
7Th GroundStar User´s Conference
How to face the optimization?
Pag : 31

32. Optimization: Back to the Core
7Th GroundStar User´s Conference
How to face the optimization?
Identify the priorities of your business core.
It´s important to initiate in an early stage the internal work with all
the stakeholders involved in the business change
WHY?
Any business requires nowadays more than never a
sustainability based in the optimal usage of the resources and
an efficient driven operation
Automates and standardize those pillars are the foundations of
any business –change project
WHAT?
Pag : 32

33. Optimization: Back to the Core
7Th GroundStar User´s Conference
How to face the optimization? : Iberia´s insight….
WHO?
Optimization involves all the layers of the company.
Identify and clarify those conflicts between business targets and
operation constraints.
Ask for feedback, feedback and feedback to all the actors involved,
Users and Managers and provide them with analitycs reports and
optimization evolution metrics.
The know-how acquired by the proffesionals involved in the
optimization model must be shared and exploded as retrofeed in
the optimization knowledge lifecycle.
Pag : 33

34. Optimization: Back to the Core
7Th GroundStar User´s Conference
How to face the optimization?
Identify your targets.
Reduce restrictions and needs to the minimum
expression.
Identify the relation between the business core
variables and the system core parameters.
Evaluate the results of the possible combinations.
1 2 3 4
HOW?
Pag : 34

35. All the areas involved in the operation are subject to optimization, but each one requires a
specific approach that implies specific system functionalities and parameters.
Optimization: Back to the Core
7Th GroundStar User´s Conference
How to face the optimization?
Two-steps optimization
Cross-utilisation
Service level
Teaming
Task combination
Task overlapping
WHERE?
Pag : 35

36. Day of operation
Short term
Optimization: Back to the Core
7Th GroundStar User´s Conference
How to face the optimization?
Medium term
Long term
Optimization must be applied in every step of the resources planification process.
Planning & Rostering Pre-Planning Real Time
The real time optimization window that is applied in the day of the operation must be defined,
deciding in which timeframe the real time users have the entire responsability.
This window may vary in contingency situations.
WHEN?
Pag : 36

37. Optimization: Back to the Core
7Th GroundStar User´s Conference
How to face the optimization?
WHAT ELSE? Next in the roadmap...
Pag : 37

38. Optimization: Back to the Core
7Th GroundStar User´s Conference
Index
1. Reasons and motivation of the optimization
2. Necessity, characterization, priorities
3. Functional design of the optimization algorithm
4. Example of an optimization model : Pax Dep.
5. Lesson learned in the IB´s optimization process
6. Future lines of development of the optimization
Pag : 38

39. Optimization: Back to the Core
7Th GroundStar User´s Conference
Short & medium term enhancement to the airport optimization problem
General inventory of new potentail optimization airport challenges
Pag : 39
ULDs allocation ( peak & valleys )
Best nightly GSE re-fuelling routes
GHE apron management & parking
Laterlals assignment based on #ULDs & # bags
Automatic Service Level assignment
The behavioral profile of the staff considered by the opt.
Online queuing at Security & passport update the travel time
Airport digital signage update by the optimizer
Cost model optimization based in penalty costs : connectivity

40. Optimization: Back to the Core
7Th GroundStar User´s Conference
The last step : The hollistic multihub approach
Pag : 40
CM
1
Mobile Optimization Immobile Optimization Aircraft Optimization
CM
1
Cost Model / Hub
CM
n
CM
2
Airline CM
&
Overall
Optimizer
Resources
Tasks
GHE
ULDs
Gates
PKNs
Fleets
Tail numbers
Local Taxes
Infrastructure Usage
GA
O
GA
O
Global Aircraft Opt.
All fleet status

42. 7Th GroundStar User´s Conference
Madrid, 12-14 of September 2012