Single Machine Scheduling with General Learning Functions: Optimal Solutions

Eren, Tamer

doi:10.5505/pajes.2013.43153

Cited by 1 publication

(3 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The number of flight segments in duty is allowed to be 2, 3, 4 and 5. The cost of each pairing is also calculated according to the equation of (1). The minimum number of crew pairing is found using the first mathematical model.…”

Section: Resultsmentioning

confidence: 99%

“…Airline scheduling and planning problems solved sequentially consist of several sub-problems: the flight schedule design, the fleet assignment, the aircraft routing, and the crew scheduling. The main objective of solving these problems is to maximization of airline's profit [1,2]. The airline sector has a narrow profit margin and fierce competition.…”

Section: Introductionmentioning

confidence: 99%

“…In managing irregular operations, flight-to-aircraft rescheduling and crew rescheduling are solved sequentially. In the solution process of the problems encountered, resolving the problem of finding the flight sequence, dividing the sequences in the problem of finding the previous flight sequence into parts, using the reserve team members and flying the team to join the flight at the airport needed in the status of a non-income passenger [1,3,4,5].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Bi-Objective Goal Programming for Airline Crew Pairing

ORHAN

2022

Eskişehir Technical University Journal of Science and Technology a - Applied Sciences and Engineering

View full text Add to dashboard Cite

The crew cost constitutes 20% of the direct operating cost in airline operations after the aircraft fuel cost. Effective crew scheduling can save tens of millions of dollars to the airlines and result in low-cost flight tickets for the passengers and improved quality of life for the crew. The crew pairing requires addressing union expectations, company rules, regulations of countries' civil aviation authorities. In this study, bi-objective goal programming is proposed to minimize the number of crew to perform flights and minimize the flight pairings cost while addressing the challenging issues mentioned above. The integer set-covering goal programming model is formulated and solved using GAMS mathematical programming software. The results showed that the bi-objective model could provide significant cost advantages to airlines. The computational experiments have been performed over a set of real data.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%