Title :
Cooperative Co-evolution with Weighted Random Grouping for Large-Scale Crossing Waypoints Locating in Air Route Network
Author :
Xiao Mingming ; Zhang Jun ; Cai Kaiquan ; Cao Xianbin ; Tang Ke
Author_Institution :
Sch. of Electron. & Inf. Eng., Beihang Univ. Beijing, Beijing, China
Abstract :
The large-scale Crossing Waypoints Location Problem (CWLP) is a crucial problem in the design of Air Route Network (ARN). CWLP is fully non-separable and non-differentiable, and thus traditional algorithms can hardly deal with it. This paper proposes an algorithm named Cooperative Co-evolution with Weighted Random Grouping (CCWR) to tackle it. CCWR employs the weighted random (WR) grouping strategy, which is specifically designed for CWLP, to divide the large-scale Crossing Waypoints (CWs) into small sub-groups and an Evolutionary Algorithm (EA) to solve the smaller scale CWs location problem in each sub-group. Experiments on the database of the ARN in China have been carried out to evaluate the performance of CCWR. The results showed that CCWR is superior to a number of state-of-the-art algorithms, and the advanced performance of CCWR is mainly due to the WR grouping strategy.
Keywords :
air traffic; evolutionary computation; group theory; transportation; ARN; CWLP; China; air route network; air traffic; cooperative co-evolution; evolutionary algorithm; large-scale crossing waypoints location problem; weighted random grouping strategy; Airports; Algorithm design and analysis; Collaboration; Educational institutions; Optimization; Safety; Vectors; Air Route Network; Cooperative Co-evolution; Crossing Waypoints Location;
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2011 23rd IEEE International Conference on
Conference_Location :
Boca Raton, FL
Print_ISBN :
978-1-4577-2068-0
Electronic_ISBN :
1082-3409
DOI :
10.1109/ICTAI.2011.40