A dual population multi-operator genetic algorithm for flight deck operations scheduling problem
It is of great significance to carry out effective scheduling for the carrier-based aircraft flight deck operations. In this paper, the precedence constraints and resource constraints in flight deck operations are analyzed, then the model of the multi-aircraft integrated scheduling problem with tran...
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Veröffentlicht in: | Journal of systems engineering and electronics 2021-04, Vol.32 (2), p.331-346 |
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Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | It is of great significance to carry out effective scheduling for the carrier-based aircraft flight deck operations. In this paper, the precedence constraints and resource constraints in flight deck operations are analyzed, then the model of the multi-aircraft integrated scheduling problem with transfer times (MAISPTT) is established. A dual population multi-operator ge-netic algorithm (DPMOGA) is proposed for solving the problem. In the algorithm, the dual population structure and random-key encoding modified by starting/ending time of operations are adopted, and multiple genetic operators are self-adaptively used to obtain better encodings. In order to conduct the mapping from encodings to feasible schedules, serial and parallel scheduling generation scheme-based decoding operators, each of which adopts different justified mechanisms in two separated populations, are introduced. The superiority of the DPMOGA is verified by simulation experiments. |
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ISSN: | 1004-4132 1004-4132 |
DOI: | 10.23919/JSEE.2021.000028 |