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Evolutionary algorithms for solving the airline crew pairing problem - ScienceDirect
Source: sciencedirect.com
Article summary:
1. The article discusses the use of evolutionary algorithms to solve the airline crew pairing problem.
2. The crew pairing problem is divided into two stages: crew pairing generation and optimisation.
3. Three evolutionary algorithms (EA) are applied to a case study from Turkey, and the results show that the memetic algorithm is an effective heuristic for solving the CPP.
Article analysis:
The article provides a comprehensive overview of the use of evolutionary algorithms for solving the airline crew pairing problem, and presents a two-stage model for this purpose. The authors provide evidence from twelve different datasets obtained from a Turkish domestic airline, which supports their claims that these algorithms can be used effectively to solve this problem.
The article does not present any counterarguments or alternative solutions to this problem, nor does it explore any potential risks associated with using these algorithms in practice. Additionally, there is no discussion of how these algorithms might be biased or limited in their application, or how they might be improved upon in future research. Furthermore, there is no mention of any ethical considerations related to using these algorithms in an industry such as aviation, where safety is paramount.
In conclusion, while this article provides a thorough overview of evolutionary algorithms for solving the airline crew pairing problem, it could benefit from further exploration into potential biases and risks associated with using these algorithms in practice, as well as exploring alternative solutions and counterarguments to its proposed approach.