Airline Crew Scheduling with Potts Neurons

Martin Lagerholm, Carsten Peterson, Bo Söderberg

NeCo 1997 pp. 1589-1599

doi:10.1162/NECO.1997.9.7.1589 /neco/1997/lagerholm1997neco-airline/

Abstract

A Potts feedback neural network approach for finding good solutions to resource allocation problems with a nonfixed topology is presented. As a target application, the airline crew scheduling problem is chosen. The topological complication is handled by means of a propagator defined in terms of Potts neurons. The approach is tested on artificial random problems tuned to resemble real-world conditions. Very good results are obtained for a variety of problem sizes. The computer time demand for the approach only grows like (number of flights)3. A realistic problem typically is solved within minutes, partly due to a prior reduction of the problem size, based on an analysis of the local arrival and departure structure at the single airports.

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Text

Lagerholm et al. "Airline Crew Scheduling with Potts Neurons." Neural Computation, 1997. doi:10.1162/NECO.1997.9.7.1589

Markdown

[Lagerholm et al. "Airline Crew Scheduling with Potts Neurons." Neural Computation, 1997.](https://mlanthology.org/neco/1997/lagerholm1997neco-airline/) doi:10.1162/NECO.1997.9.7.1589

BibTeX

@article{lagerholm1997neco-airline,
  title     = {{Airline Crew Scheduling with Potts Neurons}},
  author    = {Lagerholm, Martin and Peterson, Carsten and Söderberg, Bo},
  journal   = {Neural Computation},
  year      = {1997},
  pages     = {1589-1599},
  doi       = {10.1162/NECO.1997.9.7.1589},
  volume    = {9},
  url       = {https://mlanthology.org/neco/1997/lagerholm1997neco-airline/}
}