Air Cargo Scheduling Using Genetic Algorithms

S. Fong, M.G. da Costa, R. Khoury
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引用次数: 2

Abstract

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.
基于遗传算法的航空货运调度
本课题是在飞机承载能力范围内优化包裹调度,并对其进行仿真。以客户满意度为评价指标,使飞机的使用和利润最大化。针对航空货物分批发运调度问题,提出了三种优化算法。这些算法包括最早到期日遗传算法法、延长到期日遗传算法法和延长到期日遗传算法法。将这些算法的性能与先到先得和最早到期日调度方法进行了比较。利用适应度函数分析了遗传算法的性能。在中国城市内处理的航空货物是根据九家航空公司的航班时间表,包括澳门航空公司、长荣航空公司、国泰航空公司、中国南方航空公司、中国东方航空公司、中国国际航空公司、中国龙航空公司、中国航空公司和文华航空公司。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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