linear4 - American Airlines 15-853:Algorithms in the Real...

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1 15-853 Page1 15-853:Algorithms in the Real World Linear and Integer Programming V – Case Study: Airline Crew Scheduling 15-853 Page2 American Airlines Problem : Schedule crew (pilots and flight attendants) on flight segments to minimize cost. – over 25,000 pilots and flight attendants – over $1.5 Billion/year in crew costs Assumes the flight segments are already fixed. Methods described today : – 1970-1992: TRIP (Trip Reevaluation and Improvement Program). Local optimization given an initial guess – 1992-present? Global optimization (approximate) 15-853 Page3 Algorithms in the Real World Editor’s note from a recent paper : “A crew resource planning manager at the subject company confirmed to me that the work described in this paper has been in regular operational use since its completion, that it has been used to support labor negotiations, and that while its benefits have not been quantified, the system is an improvement over the prior system and is working well. For commercial reasons, the subject company wants to remain anonymous. 15-853 Page4 Crew Pairings Example : A 2 day crew pairing with DFW (Dallas- Fort Worth) as the base. Duty period 1 Sign in: 8:00 DFW 9:00-10:00 AUS (segment 1) AUS 11:00-13:00 ORD (segment 2) ORD 14:00-15:00 SFO (segment 3) Overlay in SFO Duty period 2 Sign in: 7:00 SFO 8:00-9:00 LAX (segment 4) LAX 10:00-11:45 SAN (segment 5) SAN 13:00-19:30 DFW (segment 6) Sign out: 19:45
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2 15-853 Page5 Properties of Pairings National pairings typically last 2 or 3 days. Crew work 4 or 5 pairings per month. Collection of pairings in a month is a Bidline. – Recent work has considered optimizing the bidlines. Today we will just discuss pairings. – Crew “bid” on the bidlines (seniority based)
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This note was uploaded on 11/09/2008 for the course COMPUTER S 15853 taught by Professor Guyblelloch during the Fall '07 term at Carnegie Mellon.

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linear4 - American Airlines 15-853:Algorithms in the Real...

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