Parallel evolutionary algorithms and neural networks were used to solve complex optimisation problems in schedule planning at large internationally operating network oriented airlines and to model passenger demand in service planning. Results comprise a market share model based on neural networks, a framework for service planning, a calibration tool, and optimisation procedures for solving fleet assignment and tail assignment problems. These results have been incorporated into the NetSched product line which is marketed world wide by Lufthansa Systems. Of scientific interest regarding the potential of evolutionary algorithms to solve complex optimisation problems of practical value is the SPCM-hypothesis regarding the necessity of employ specific problem-adapted complex mutation operators. (orig.)SIGLEAvailable from TIB Hannover: F99B1213+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekBundesministerium fuer Bildung und Forschung (BMBF), Bonn (Germany)DEGerman
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