This paper addresses the optimization of flight crew assignments by introducing a mathematical optimization model aimed at maximizing the allocation of flight crew to flights while minimizing overall occurrences and the use of substitute qualifications. The proposed approach involves route-based clustering, where flight routes are aggregated around hub airports to serve as the fundamental unit for matching flight crew. This transforms the problem of flight crew assignment into a route-based matching scenario. A mathematical programming model is established to minimize the number of unfulfilled crew assignments, flight occurrences, and substitute qualification usage, while also prioritizing these objectives. To enhance computational efficiency, a simulated annealing algorithm and a novel heuristic strategy are employed for solving. Results demonstrate the superiority of the new heuristic strategy over simulated annealing. Specifically, for dataset A, 202 flights were successfully scheduled with no crew occurrences or substitute qualification usage. For dataset B, 13235 flights were successfully arranged with zero crew occurrences or substitute qualification usage, and the program execution time was 0.32s.
A Study of Crew Allocation Based on a Novel Heuristic Algorithm and Simulated Annealing Algorithm
28.06.2024
1111164 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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