Air Cargo Scheduling using Genetic Algorithms

被引:0
作者
Fong, Simon [1 ]
Da Costa, Miguel Gomes, Jr. [1 ]
Khoury, Richard [2 ]
机构
[1] Univ Macau, Dept Comp & Informat Sci, Macau, Peoples R China
[2] Lakehead Univ, Dept Software Engn, Thunder Bay, ON P7B 5E1, Canada
来源
2013 INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL AND BUSINESS INTELLIGENCE (ISCBI) | 2013年
关键词
genetic algorithms; scheduling;
D O I
10.1109/ISCBI.2013.41
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This 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.
引用
收藏
页码:170 / 173
页数:4
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