Improved genetic algorithm for aircraft departure sequencing problem

被引:3
作者
Wang Lai-jun [1 ]
Hu Da-wei [1 ]
Gong Rui-zi [2 ]
机构
[1] Changan Univ, Sch Automobile, Xian 710064, Shaanxi, Peoples R China
[2] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China
来源
THIRD INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTING | 2009年
关键词
departure sequencing; adaptive genetic algorithms; total probability crossover; wake vortex separation;
D O I
10.1109/WGEC.2009.125
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Optimization model is build for solving the aircraft departure sequencing problem (DSP) in this paper first. Then, an improved genetic algorithm (Improved GA) using symbolic coding is proposed, where a type of total probability crossover and big probability mutation are performed. In this way, the evolutionary policy of PSO is absorbed into IGA, which reduces the complexity and enhance the efficiency greatly. Last, a simulation program using basic genetic algorithm (Basic GA), adaptive genetic algorithm (Adaptive GA), and IGA is performed. The simulation result shows that the model is effective and Improved GA has better performance than Basic GA or Adaptive GA.
引用
收藏
页码:35 / +
页数:2
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