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. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 1 crew rostering 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-planning more flexible and creates additional cash flow OPS OPS OPS OPS OPS OPS Roster publication Time To Market

3. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 2 Requests/Bids Early roster information Personnel restrictions Roster stability Text Qualifications Quality demands Additional regulations Special agreements to the flight schedule COC/CAB guidelines 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

4. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 3 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 flexible as 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 World Manual, rule oriented process New world Objective 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)

5. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 4 Quality check Quality check Manual planning day by day according 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 worldwithout optimizer ACA reference runs ACA production runs New worldwith optimizer ACA < 2 weeks ca. 3,5 weeks Create pre-roster … Same starting pointDefinable end point

6. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 5 Manual and automatic rostering were compared with measuring time need and quality Zeit Manual crew rostering Duplication Pre- roster Same starting point Automatic crew rostering Finished roster 1 Compare quality Planner 1 User of standard rostering system Planner 2 User of standard rostering system User of optimizer ACA Finished roster 2 7 CAB groups 5 COC groups Compare time need

7. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 6 Acceptance test as 12 real matches between two planners Planner 1 User of CAS Measuring quality with objective function _ : _ CAS ACA CAS Planner 2 User of CAS User of ACA

8. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 7 Generation of one solution Manual plan Measuring the quality with the official acceptance objective function means only to compare two numbers GeneratorSolver Number of roster day CRM1 CRM2 CRM3 Optimizer ACA day CRM1 CRM2 CRM3 Solution with points = x Best roster Generates a lot of solutions Picks out the best solution (lowest points according to the objective function) day CRM1 CRM2 CRM3 Solution with points = y Manual solution can also be evaluated with objective function Compare numbers 3 cases possible x<y (new world better) x=y(old and new is the same) x>y (old world is better)

9. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 8 In all cases the planner with the optimizer was able to produce better rosters in shorter time 0 : 12 CASACACAS

10. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 9 Points (OPPs) Old world Points (OPPs) New world FB DUS Aug0412.597.327 (18)293.992 (0) FB FRA NG IK Aug041.275.565 (0)1.166.205 (0) FB FRA NB Gem Aug041.273.005 (0)952.758 (0) FB DUS Sep0441.358.431 (69)2.603.397 (38) FB FRA NG IK Sep049.071.263 (5)717.050 (0) FB FRA NG Gem Sep041.398.269 (0)1.068.476 (0) FB DUS Okt041.461.927 (12)533.739 (1) Overview of CAB results Result objective function ACACAS OPPs = Number of Open Positions Time need: 2-7 days Time need: 2-4 hours

11. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 10 Detailed comparison of objective function result manual and automatic roster for a flight attendant planning group Aug04 Manual rosterACA roster Points FB FRA NB Gem Aug04Sum points1.273.005952.758 Additional flying hoursKPI2480.971475.972 LSW hours lower limitKPI4424.832278.524 LSW hours higher limitKPI580.0000 BZW hours lower limitKPI6197.431149.471 BZW hours higher limitKPI74.7700 Destination diversityKPI141010 Consecutive days-offKPI1539.54035.630 Days-off above claimKPI1845.36013.160 Aircraft diversityKPI2100 Open position points 00 Overlapping open positions 00 ACA CAS Size: 835 crewmembers

12. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 11 Comparison of days-off corridor between manual and automatic roster for a flight attendant planning group Aug04 Manual Automatic Number of crewmember Number of days-off above claim

13. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 12 Comparison of flying hours corridor between manual and automatic roster for a flight attendant planning group Aug04 Manual Automatic Number of crewmember Number of flying hours Automatic roster: Sharper and higher peak at lower flying hour level „fair distribution of workload“

14. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 13 Manual Automatic Number of crewmember Number of flying hours Comparison of flying hours corridor between manual and automatic roster for a flight attendant planning group Sep04

15. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 14 Due to measurable results we (IT department) were able to convince the planning department

16. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 15 Overview of ACA usage in March 2006 für planning month April 2006 Week-end Roster publication Bidding phase

17. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 16 Any questions?

18. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 17 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 manual rosterExample ACA roster

19. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 18 Zielfunktion: Beispiel Mehrflugstunden cost=100 * nbr_of_extra_hours (extra_hours=bzw > 70) Roster combination 1: cost=100 * 5 + 100 * 0 = 500 Mehrflugstunden: 5 Roster combination 2: cost=100 * 2 + 100 * 0 = 200 Mehrflu g stunden: 2

20. AGIFORS Crew Management Study Group 2006 Conference April 9 - 12, 2006, HonoluluPage 19 Abstract End of 2005 the automatic rostering tool ACA at Deutsche Lufthansa was officially accepted by the crew-planning department. A prerequisite for a successful use was to convince crew-planning that they have an improvement by using ACA, i.e. making better rosters in a shorter time. This was reached by several real competitions between manual and automatic planning. At the end it was proven that in all cases the planner with an automatic rostering tool produced better rosters in a shorter time. Now the tool is accepted by the users even some of the users have developed a real gambling: "Let's play!"