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(Airline Crew Scheduling Problem (CSP

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Airline Crew Scheduling Problem (CSP) Ahmad Khayer Dastjerdi 256622

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Review ~ Introduction » Scheduling Process * Airline Crew Scheduling Problem » Model » Solution Approaches » Case Study

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Introduction: * Airline crew scheduling is a well-studied field in OR. * Second cost-relevant factor after fuel * Misunderstanding and disharmonies among the crew : negative effect on the airline's customers. * Highly competitive global market SE ee eer ee ee een nee

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Introduction (Con’d) Dominant driving forces for airline companies : * Cost Minimization * Customer Satisfaction Other important fields: ماك ةا" Training of staff - Employee satisfaction معصهصهکنهم خصمعو جوا عوماء عطا ومتلامء : عه19۵ وصنقهما (18)2002 حهصءه/1(۳ ‎UGE mV CCB IES Cag)‏ ۷

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:Scheduling Process -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. 0 Wile nees MG Rel cp NECN Da iytta weet lce cite elie ictmiy to Mero rer Cpe + 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, 0

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5 2 Block and ‎Dus cGy‏ صمت یت نیت ‏وتات مهو د نت ‎SON Str evrene ted 8‏ 0020200000 ين 05 4 وستصمهام طتعهممع. يي ا 2 ‎Bares ates‏ ‎Scheduling Assignment‏ ‏منم همه ‎1 ee cee coer ENC Te eae Pee Seo ‏معمهلا 61 ععكناقطصءل!‎ 881 )2003(

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: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 ‏توافت ار‎ 0 crew members stationed ‏ةا‎ 0 (BALAJI GOPALAKRISHNAN, ELLIS. L. JOHNSON 2005) 00 rae juling approach with tim een creer ent ott

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: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.

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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. one eat ease Reon ne rc neem Om CCRC ctr eee Len eer ae NC COS EL, Klabjan D, Nemhauser GL, Vance PH (2003) Oe caer meee te ee UCL Ce MCT Nace enV TiCtcd Routing Problem. ( Mellouli 2001)

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Roster Example dayt day2 day3 day4 dayS 2۱ [ 0 2 Roster ‎cays,‏ اجه ‎23:59 ‎ ‎ ‎ ‎ ‎ ‎ ‎ ‎Flight duty ‎ ‎17:35 ‎emt | Flight ‎ ‎ ‎ ‎ ‎ ‎ ‎ ‎17:38 ‎ ‎ ‎ ‎ ‎ ‎ ‎ ‎ ‎ ‎ ‎ ‎ ‎ ‎ ‎ ‎

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:The Crew Scheduling Problem * Crew Pairing, Problem (CPP) * Crew Assignment Problem (CAP) or airline Crew Rostering Problem (CRP) ا وسهای)خهمناههج0 ما وحتصصعاط همق وصتلعلعطع۹ مدع ماعته

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

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‘An example ای ره ۱ اف کی ۰ i 8 7 6 0 A ‏مكب السك ا‎ cre (ec ‏تكو‎ ‏م ل‎ 1۹0 11:30- 10:00- roe 1230 11:00 The second plane flies between Atlanta and New York ۳ I H G 3 ۸ ee 7 1۳92 ore 14:30- 12:00- 0 The third plane goes on alAtlanta, New'¥6tk, MetiPhis |Atlanta 0 0 ‏ان رد‎ 8 K Mem Ad | ۱۱ rena Mem=Ad | NY—-Mem | au—Nv Yanserere 7 ae 11:45- ۳۳7 9 14:00 120 AB,CD,EF,GH.U,KLM,NOP for total cost 6.25 ABCDEF,GHI,KLMNOP for total cost 6.00 AB, CDU, GHEF, KLMNOP for total cost 4.75

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

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Model for crew assignment problem Pter ces arc rps eon e Cer eset Claude P. Medard Nidhi Sawhney, An integrated aircraft routing, crew scheduling and flight retiming model (Anne Mercier, Francois Soumis 2005)

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:Solution approach * Constructive heuristics * Mathematical Programming Branch-and-Bound Branch-and-Cut ۰ Network-based Models * Meta-Heuristics ۱6/۶ ۱ Simulated Annealing

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۱۱0 Hotel stays Transit Hotel cost Transit cost Total cost ete (% 100 100 100 100 100 Manual )schedule mene nace ty 3 Autom. )Schedule 27 76.29 113.16 61.93 106.38 88.50 Serer se Case study: (European tourist airline) Total %) Saving ( DS 13.16- 38.07 6.58- 11.50 Tee eee ‏ممم‎ 5 Suhl, Markus P. Thiel 2} price 0 erring! and multipl Yufeng Guo|

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Thank you for your attention

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