Method of sector optimum partition based on controller workload

ZHANG Ming; HAN Song-chen

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ZHANG Ming, HAN Song-chen. Method of sector optimum partition based on controller workload[J]. Journal of Traffic and Transportation Engineering, 2005, 5(4): 86-89.

Citation:

ZHANG Ming, HAN Song-chen. Method of sector optimum partition based on controller workload[J]. Journal of Traffic and Transportation Engineering, 2005, 5(4): 86-89.

ZHANG Ming, HAN Song-chen. Method of sector optimum partition based on controller workload[J]. Journal of Traffic and Transportation Engineering, 2005, 5(4): 86-89.

Citation:

ZHANG Ming, HAN Song-chen. Method of sector optimum partition based on controller workload[J]. Journal of Traffic and Transportation Engineering, 2005, 5(4): 86-89.

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Method of sector optimum partition based on controller workload

School of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

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Author Bio:
Zhang Ming(1975-), male, lecturer, 86-25-84893716, zhangming_nuaa@126.com
Received Date: 2005-08-10
Publish Date: 2005-12-25

Abstract

Abstract

In order to ensure flight security and increase airspace capability, in according to the balance rule of controller workload, a simulated annealing algorithm was adopted to solve sector optimum partition, which was based on the statistic method of controller workload and the mathematical model describing airspace topology structure. The new resolution satisfied the restriction of the three rules for airspace partition, they were preferential search, sector continuity and the minimum of sector number. The optimum result of Xiamen control airspace shows that the maximal workload difference among three sectors is 4.1 s, the value is smaller than 17.5 s, which indicates that the method is feasible.
- airspace planning,
- sector optimum partition,
- simulated annealing algorithm,
- control workload,
- airspace topology structure

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References(4)

References

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[2]	Delahaye D, Schoenauer M, Alliot J M. Airspace sectoring by evolutionary computation[A]. Proceeding of 10th IEEE Conference on Artificial Intelligence for Applications[C]. New York: IEEE, 1998.
[3]	Delahaye D, Alliot J M, Schoenauer M, et al. Genetic algorithms for partitioning airspace[A]. Proceeding of 10th IEEE Conference on Artificial Intelligence for Applications[C]. New York: IEEE, 1994.
[4]	Han Song-chen, Zhang Ming, Huang Wei-fang. Method and computer technique for control sector optimum partition[J]. Journal of Traffic and Transportation Engineering, 2003, 3(1): 101—104. (in Chinese) http://transport.chd.edu.cn/article/id/200301023