Airline Crew Scheduling with Potts Neurons

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Standard

Airline Crew Scheduling with Potts Neurons. / Lagerholm, Martin; Peterson, Carsten; Söderberg, Bo.

I: Neural Computation, Vol. 9, Nr. 7, 01.10.1997, s. 1589-1599.

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

Harvard

Lagerholm, M, Peterson, C & Söderberg, B 1997, 'Airline Crew Scheduling with Potts Neurons', Neural Computation, vol. 9, nr. 7, s. 1589-1599.

APA

Lagerholm, M., Peterson, C., & Söderberg, B. (1997). Airline Crew Scheduling with Potts Neurons. Neural Computation, 9(7), 1589-1599.

CBE

Lagerholm M, Peterson C, Söderberg B. 1997. Airline Crew Scheduling with Potts Neurons. Neural Computation. 9(7):1589-1599.

MLA

Lagerholm, Martin, Carsten Peterson, och Bo Söderberg. "Airline Crew Scheduling with Potts Neurons". Neural Computation. 1997, 9(7). 1589-1599.

Vancouver

Lagerholm M, Peterson C, Söderberg B. Airline Crew Scheduling with Potts Neurons. Neural Computation. 1997 okt 1;9(7):1589-1599.

Author

Lagerholm, Martin ; Peterson, Carsten ; Söderberg, Bo. / Airline Crew Scheduling with Potts Neurons. I: Neural Computation. 1997 ; Vol. 9, Nr. 7. s. 1589-1599.

RIS

TY - JOUR

T1 - Airline Crew Scheduling with Potts Neurons

AU - Lagerholm, Martin

AU - Peterson, Carsten

AU - Söderberg, Bo

PY - 1997/10/1

Y1 - 1997/10/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0004688683&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0004688683

VL - 9

SP - 1589

EP - 1599

JO - Neural Computation

JF - Neural Computation

SN - 1530-888X

IS - 7

ER -