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

1. How to convince crew planners to use an automatic rostering tool (ACA) Crew Management Study Group 2006 Conference Honolulu, April 9 - 12, 2006

2. Shortening the crew rostering process makes the network-planningmore flexible and creates additional cash flow OPS Market changes / booking trend Old world: Flight-schedule-optimization Roster publication network-planning crew rostering OPS Time To Market New world: Flight-schedule-optimization Roster publication OPS network-planning crew rostering Time To Market 3 weeks

3. Crew rostering at Lufthansa is each month a challenge to find a balance between company requirements and individual interests Legality Crewmember Irregularities Text • Requests/Bids • Early roster information • Personnel restrictions • Roster stability • JAR- and LBA-regularities • MTV, BVB, OM-A • Flight plan changes (e.g. fleet changes) • Notification of illness • Capacitiy changes between different home bases Text COC/CABguidelines LH-efficiency • Later delivery of flight schedule • Economic efficiency • Operational stability • Producing on time • Individual roster stability • Qualifications • Quality demands • Additional regulations • Special agreements to the flight schedule Text Text

4. To speed up the process and to obey all objectives the crew rostering process has to change New worldObjective oriented process Old WorldManual, rule oriented process • 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) • 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)

5. Createpre-roster Createpre-roster Former manual and new automatic crew rostering process have the same starting point and a definable end point • Old world without optimizer Manual planning day by dayaccording to well.defined chain of decisions Quality check Same starting point Definable end point ca. 3,5 weeks • New world with optimizer ACA ACA reference runs ACA production runs Quality check … < 2 weeks

6. Manual and automatic rostering were compared with measuring time need and quality • Planner 1 • User of standard rostering system Pre-roster Finishedroster 1 Manual crew rostering Duplication Pre-roster Same starting point Compare time need Compare quality Duplication • Planner 2 • User of standard rostering system • User of optimizer ACA 7 CAB groups 5 COC groups Finishedroster 2 Pre-roster Automatic crew rostering Zeit

7. CAS CAS Acceptance test as 12 real matchesbetween two planners • Planner 1 • User of CAS • Planner 2 • User of CAS • User of ACA _ : _ ACA Measuring quality with objective function

8. day CRM1 CRM2 CRM3 day CRM1 CRM2 CRM3 Measuring the quality with the official acceptance objective function means only to compare two numbers Optimizer ACA Solution withpoints = x Generator Solver Number ofroster Bestroster Generates a lot of solutions Picks out the best solution (lowest points according to the objective function) 3 cases possible x<y (new world better) x=y(old and new is the same) x>y (old world is better) Compare numbers Manual solution can also be evaluated with objective function Manual plan Solution withpoints = y Generation of one solution day CRM1 CRM2 CRM3

9. CAS CAS ACA In all cases the planner with the optimizer was able to produce better rosters in shorter time 0 : 12

10. Resultobjective function CAS CAS ACA Overview of CAB results Time need:2-7 days Time need:2-4 hours OPPs = Number of Open Positions

11. CAS CAS ACA Detailed comparison of objective function result manual and automatic roster for a flight attendant planning group Aug04 Size:835 crewmembers

12. Comparison of days-off corridor between manual and automatic roster for a flight attendant planning group Aug04 Automatic Number ofcrewmember Manual Number ofdays-off above claim

13. Comparison of flying hours corridor between manual and automatic roster for a flight attendant planning group Aug04 Automatic roster:Sharper and higher peak at lowerflying hour level „fair distribution of workload“ Automatic Number ofcrewmember Manual Number offlying hours

14. Comparison of flying hours corridor between manual and automatic roster for a flight attendant planning group Sep04 Automatic Number ofcrewmember Manual Number offlying hours

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

16. Overview of ACA usage in March 2006 für planning month April 2006 Bidding phase Roster publication Week-end Week-end Week-end Week-end

17. Any questions?

18. All elements of an objective function have to be calibrated against each other 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 ACA roster Example manual roster