Air cargo scheduling using genetic algorithms
Fong,Simon1; Da Costa,Miguel Gomes1; Khoury,Richard2
Source PublicationProceedings - 2013 International Symposium on Computational and Business Intelligence, ISCBI 2013
AbstractThis project is to optimize the scheduling of the packages within the aircrafts' loading capacities, which are simulated. The optimization criteria are evaluated by customer satisfaction and maximize the usage and profit of the aircrafts. Three algorithms for the batch delivery scheduling problem are developed to find the optimal air cargo shipment. These algorithms are genetic algorithm with earliest due date method, extended due date method and genetic algorithm with extended due date method. The performances of these algorithms are compared to first come first serve and earliest due date scheduling method. The performance of genetic algorithm is analyzed by its fitness function. Air cargos which are handled within Chinese cities is based on flight schedules of nine airline companies including Air Macau, EVA Airways, Cathay Pacific, China Southern Airlines, China Eastern Airlines, Air China, Dragon Air, China Airlines and Mandarin Airlines. © 2013 IEEE.
KeywordGenetic algorithms Scheduling
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Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.Department of Computer and Information Science, University of Macau,Macao
2.Department of Software Engineering, Lakehead University,Thunder Bay,Canada
First Author AffilicationUniversity of Macau
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GB/T 7714
Fong,Simon,Da Costa,Miguel Gomes,Khoury,Richard. Air cargo scheduling using genetic algorithms[C],2013:170-173.
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