Multi-objective Evolutionary Approach to Aircraft Landing Scheduling Problems

被引：0

作者：

Tang, Ke ^{[1
]}

Wang, Zai ^{[1
]}

Cao, Xianbin ^{[1
]}

Zhang, Jun ^{[2
]}

机构：

[1] Univ Sci & Technol China, Dept Comp Sci & Technol, Nat Inspired Computat & Applicat Lab, Hefei 230027, Anhui, Peoples R China

[2] Beihang Univ, Sch Elect Informat Engn, Beijing 100083, Peoples R China

来源：

2008 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-8 | 2008年

基金：

中国国家自然科学基金;

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Scheduling aircraft landings has been a complex and challenging problem in air traffic control for long time. In this paper, we propose to solve the aircraft landing scheduling problem (ALSP) using multi-objective evolutionary algorithms (MOEAs). Specifically, we consider simultaneously minimizing the total scheduled time of arrival and the total cost, and formulate the ALSP as a 2-objective optimization problem. A MOEA named Multi-Objective Neighborhood Search Differential Evolution (MONSDE) is applied to solve the 2-objective ALSP. Besides, a ranking scheme named non-dominated average ranking is also proposed to determine the optimal landing sequence. Advantages of our approaches are demonstrated on two example scenarios.

引用

页码：3650 / +

页数：2

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