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Dynamic airspace sectorization via improved genetic algorithm 被引量:6
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作者 Yangzhou Chen Hong Bi +1 位作者 Defu Zhang Zhuoxi Song 《Journal of Modern Transportation》 2013年第2期117-124,共8页
This paper deals with dynamic airspace sectorization (DAS) problem by an improved genetic algorithm (iGA). A graph model is first constructed that represents the airspace static structure. Then the DAS problem is ... This paper deals with dynamic airspace sectorization (DAS) problem by an improved genetic algorithm (iGA). A graph model is first constructed that represents the airspace static structure. Then the DAS problem is formulated as a graph-partitioning problem to balance the sector workload under the premise of ensuring safety. In the iGA, multiple populations and hybrid coding are applied to determine the optimal sector number and airspace sectorization. The sector constraints are well satisfied by the improved genetic operators and protect zones. This method is validated by being applied to the airspace of North China in terms of three indexes, which are sector balancing index, coordination workload index and sector average flight time index. The improvement is obvious, as the sector balancing index is reduced by 16.5 %, the coordination workload index is reduced by 11.2 %, and the sector average flight time index is increased by 11.4 % during the peak-hour traffic. 展开更多
关键词 dynamic airspace sectorization (DAS) Improved genetic algorithm (iGA) Graph model Multiple populations Hybrid coding Sector constraints
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