Airline Crew Scheduling Problem ‍‍(CSP) Ahmad Khayer Dastjerdi

Review  Introduction  Scheduling Process  Airline Crew Scheduling Problem  Model  Solution Approaches  Case Study

Introduction: Airline crew scheduling is a well-studied field in OR. fuel Second cost-relevant factor after fuel Misunderstanding and disharmonies among the crew : negative effect on the airline's customers. Highly competitive global market Hackman JR(2002) Leading Teams : setting the stage for great performance, Ailine crew scheduling from planning to operation (Claud p. Medard and Nidhi Sawhney)

Dominant driving forces for airline companies : Cost Minimization Customer Satisfaction Other important fields : Recruiting Training of staff Employee satisfaction 1)Hackman JR(2002) Leading Teams : setting the stage for great performance 2)airlinecrew scheduling from planning to operation (Claud p. Medard and Nidhi Sawhney) Introduction (Con’d)

Scheduling Process: profitmaximized -The main business of an airline is to offer and execute flights in such a way that profit is maximized -Underlying scheduling tasks that need to be fulfilled: Which flights are offered. When and how often such flights should take place. Which resources are allocated at which scheduling step. How the schedule execution is controlled and unpredictable events are handled. 1) Branch-and-Price Column:Generation for Solving Huge Integer Programs. Barnhart C, Cohn AM, Johnson EL, Klabjan D, Nemhauser GL, Vance PH (2003)

Block and ground time estimation Demand estimation N etwork planning Capacity planning Fleet Assignment Aircraft routing Flight Scheduling Crew Scheduling Physical aircraft scheduling Ground operation scheduling Operational time rescheduling Branch-and-Price Column:Generation for Solving Huge Integer Programs. Barnhart C, Cohn AM, Johnson EL, Klabjan D, Nemhauser GL, Vance PH (2003) Scheduling Process

Airline Crew Scheduling Problem (CSP): The largest scheduling problem Its task is to assign all flights of a given timetable together with further activities to a limited number of crew members stationed at one or several home bases. Airline Crew Scheduling: State-of-the-Art (BALAJI GOPALAKRISHNAN, ELLIS. L. JOHNSON 2005) A partially integrated airline crew scheduling approach with time-dependent crew capacities and multiple home bases(Yufeng Guo,Taieb Mellouli, Leena Suhl, Markus P. Thiel 2005)

Basic definitions: A flight leg: is a non-stop air transit from a departure airport to its corresponding destination airport. A flight duty: is a series of flight legs that can be serviced by one crew member within a workday (24 hours). A transit: occurs if the crew members' time-dependent location does not equal to the next scheduled location. A pairing: which starts from and returns to the crew member’s home base. Its maximum duration is limited by a given upper bound, e.g..five working days.

Pre-scheduled activities : like vacation, simulation, training; medical examinations, etc. represent activities that a crew member has to undertake without exception. A roster or line-of-work (LOW): represents a potential crew schedule for a dedicated crew member of the planning periods of usually two or four weeks. Branch-and-Price Column:Generation for Solving Huge Integer Programs. Barnhart C, Cohn AM, Johnson EL, Klabjan D, Nemhauser GL, Vance PH (2003) A Network Flow Approach to Crew Scheduling based on an Analogy to a Train/Aircraft Maintenance Routing Problem. ( Mellouli 2001) Mellouli 2001, Barnhart et al. 2003

Roster Example

The Crew Scheduling Problem:  Crew Pairing Problem (CPP)  Crew Assignment Problem (CAP) or airline Crew Rostering Problem (CRP) Airline Crew Scheduling From Planning to Operations(Claude P. Medard Nidhi Sawhney), Barnhart et al., 1999

min Model for crew pairing problem: Airline Crew Scheduling: State-of-the-Art BALAJI GOPALAKRISHNANELLIS. L. JOHNSON(2005)

An example: Suppose an airline has three planes based in Atlanta The second plane flies between Atlanta and New York The third plane goes on a Atlanta, New York, Memphis, Atlanta Up to 4 hours: 75% base rate 4 to 8 hours: 100% base rate Above 8 hours: 200% base rate F ٍEٍEٍEٍEDCBA Mia -- Atl Atl -- Mia Mia -- Atl Atl -- Mia Mia -- Atl Atl -- Mia 16:00-17:0014:30-15:3013:00-14:0011:30-12:3010:00-11:008:30-9:30 JIHG N.Y. -- Atl Atl -- N.Y. N.Y. -- Atl Atl -- N.Y. 17:00-19:0014:30-16:3012:00-14:009:30-11:30 P ٍOٍOٍOٍONMLK Mem -- Atl N.Y -- Mem Atl -- N.Y. Mem -- Atl N.Y -- Mem Atl -- N.Y. 18:15-19:3017:00-18:0014:30-16:3011:45-14:0011:30-12:309:00-11:00 AB,CD,EF,GH,IJ,KLM,NOP for total cost 6.25 ABCDEF,GHIJ,KLMNOP for total cost 6.00 AB, CDIJ, GHEF, KLMNOP for total cost 4.75

Is there a cheaper combination available? In order to be certain, we would have to check all pairings In order to be certain, we would have to check all pairings

min Model for crew assignment problem: Airline Crew Scheduling From Planning to Operations Claude P. Medard Nidhi Sawhney,An integrated aircraft routing, crew scheduling and flight retiming model (Anne Mercier, François Soumis 2005)

Solution approach:  Constructive heuristics  Mathematical Programming Branch-and-Bound Branch-and-Bound Branch-and-Cut Branch-and-Cut  Network-based Models  Meta-Heuristics Genetic Algorithms Genetic Algorithms Simulated Annealing Simulated Annealing

Case study : (European tourist airline) TotalSaving(%) Autom. Schedule(%) Manual schedule(%) instance Hotel stays Transit Hotel cost Transit cost Total cost A partially integrated airline crew scheduling approach with time-dependent crew capacities and multiple home bases Yufeng Guo,Taieb Mellouli, Leena Suhl, Markus P. Thiel 2005

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