how to convince crew planners to use an automatic rostering tool (aca) crew management study group...

How to convince crew planners to use an automatic rostering tool (ACA)

Crew Management Study Group 2006 Conference

Honolulu, April 9 - 12, 2006

AGIFORS Crew Management Study Group 2006 ConferenceApril 9 - 12, 2006, Honolulu

crew rostering

crew rostering

network-planning

network-planning

Flight-schedule-optimization

3 weeks

Old world:

New world:

Market changes / booking trend

Flight-schedule-optimization

Shortening the crew rostering process makes the network-planningmore flexible and creates additional cash flow

OPS

OPS

OPS

Roster publication

Roster publication

Time To Market

Time To Market


• Requests/Bids

• Early roster information

• Personnel restrictions

• Roster stability

Text Text

Text

Text

• Qualifications

• Quality demands

• Additional regulations

• Special agreements to the flight schedule

COC/CABguidelines

• Flight plan changes (e.g. fleet changes)

• Notification of illness

• Capacitiy changes between different home bases

Irregularities• JAR- and LBA-regularities

• MTV, BVB, OM-A

Legality

Crewmember

• Later delivery of flight schedule

• Economic efficiency

• Operational stability

• Producing on time

• Individual roster stability

LH-efficiency

Crew rostering at Lufthansa is each month a challenge to find a balance between company requirements and individual interests


To speed up the process and to obey all objectives the crew rostering process has to change

• Manual sequential process-> Long running time of rostering

• Static rules (must rules)

• In reality planner reacts more flexibleas documented (scope of interpretation)-> Hard to implement in software

• Employee satisfaction will override profitability

• Planner reacts due to a clear decision –making process (sophisticated crew assignment system = CAS user)

• Production of one solution is the result of a well-defined chain of decisions

• Planner can explain the solution to crewmember (->excuse)

Old WorldManual, rule oriented process

New worldObjective oriented process

• Rostering has high management attention-> High demands on transparency and measurability

• Net mgmt. forces to minimize „time to market“

• Parallel process (Use optimization tool ACA)-> Short running time of rostering

• Hard and soft rules (constraints and objective function elements)

• Controlling claims simulations-> Production of several solutions

• Finding the best solution, i.e. what is a good roster?-> Definition/calibration of an objective function

• Planner becomes operations research specialist (sophisiticated CAS + ACA user)


Qualitycheck

Qualitycheck

Manual planning day by dayaccording to well.defined chain of decisions

Former manual and new automatic crew rostering process have the same starting point and a definable end point

Old world without optimizer

ACAreferenceruns

ACAproductionruns

New world with optimizer ACA

< 2 weeks

ca. 3,5 weeks

Createpre-roster

… Createpre-roster

Same starting point Definable end point


Manual and automatic rostering were compared with measuring time need and quality

Zeit

Manual crew rostering

Duplicat

ion

Duplication

Pre-roster

Pre-roster

Pre-roster

Same starting point

Automatic crew rostering

Finishedroster 1

Compare quality

Planner 1• User of standard rostering system

Planner 2• User of standard rostering system• User of optimizer ACA

Finishedroster 2

7 CAB groups5 COC groups

Compare time need


Acceptance test as 12 real matchesbetween two planners

Planner 1

• User of CAS

Measuring quality with objective function

_ : _CAS ACA CAS

Planner 2

• User of CAS

• User of ACA


Generation of one solution

Manual plan

Measuring the quality with the official acceptance objective function means only to compare two numbers

Generator SolverNumber of

roster

dayCRM1CRM2CRM3

Optimizer ACA

dayCRM1CRM2CRM3

Solution withpoints = x

Bestroster

Generates a lot of solutions

Picks out the best solution (lowest points according to

the objective function)

dayCRM1CRM2CRM3

Solution withpoints = y

Manual solution can also be evaluated with objective function

Compare numbers3 cases possiblex<y (new world better)

x=y(old and new is the same)x>y (old world is better)


In all cases the planner with the optimizer was able to produce better rosters in shorter time

0 : 12CAS ACA CAS


Points (OPPs)Old world

Points (OPPs) New world

FB DUS Aug04 12.597.327 (18) 293.992 (0)

FB FRA NG IK Aug04 1.275.565 (0) 1.166.205 (0)

FB FRA NB Gem Aug04 1.273.005 (0) 952.758 (0)

FB DUS Sep04 41.358.431 (69) 2.603.397 (38)

FB FRA NG IK Sep04 9.071.263 (5) 717.050 (0)

FB FRA NG Gem Sep04 1.398.269 (0) 1.068.476 (0)

FB DUS Okt04 1.461.927 (12) 533.739 (1)

Overview of CAB results

Resultobjective function

ACA CASCAS

OPPs = Number of Open Positions

Time need:2-7 days

Time need:2-4 hours


Detailed comparison of objective function result manual and automatic roster for a flight attendant planning group Aug04

Manual roster ACA roster

Points Points

FB FRA NB Gem Aug04 Sum points 1.273.005 952.758

Additional flying hours KPI2 480.971 475.972

LSW hours lower limit KPI4 424.832 278.524

LSW hours higher limit KPI5 80.000 0

BZW hours lower limit KPI6 197.431 149.471

BZW hours higher limit KPI7 4.770 0

Destination diversity KPI14 101 0

Consecutive days-off KPI15 39.540 35.630

Days-off above claim KPI18 45.360 13.160

Aircraft diversity KPI21 0 0

Open position points 0 0

Overlapping open positions 0 0

ACA CASCASSize:

835 crewmembers


Comparison of days-off corridor between manual and automatic roster for a flight attendant planning group Aug04

Manual

Automatic

Number ofcrewmember

Number ofdays-off above claim


Comparison of flying hours corridor between manual and automatic roster for a flight attendant planning group Aug04

Manual

Automatic

Number ofcrewmember

Number offlying hours

Automatic roster:Sharper and higher peak at lower

flying hour level„fair distribution of workload“


Manual

Automatic

Number ofcrewmember

Number offlying hours

Comparison of flying hours corridor between manual and automatic roster for a flight attendant planning group Sep04


Due to measurable results we (IT department) were able to convince the planning department


Overview of ACA usage in March 2006 für planning month April 2006

Overview ACA use

0

10

20

30

40

50

60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Day of month (March 2006)

Nu

mb

er o

f A

CA

ru

ns

COC

CAB

KONT

Wee

k-en

d

Wee

k-en

d

Wee

k-en

d

Wee

k-en

d

Ro

ste

r p

ub

lica

tio

n

Bidding phase


Any questions?


All elements of an objective function have to be calibrated against each other

iii

n

ii

CLAIMABOVEDAYSFREEHOURSFLYINGADDTSROSTERPOIN

POINTSPOSITIONOPENTSROSTERPOINPOINTS

_____

__1

Adobe Acrobat 7.0 Document

The objective function consists of

Roster points (quality of a single roster)– Number of additional flying hours and number of days-off above claim– Deviation from target corridor (flying hours, duty days) – Destination / aircraft diversity – Number of consecutive days-off

Open position points– Number of duty days which couldn’t be assigned

Example manual roster

Adobe Acrobat 7.0 Document

Example ACA roster

how to convince crew planners to use an automatic rostering tool (aca) crew management study group...

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