By Topic

Solving Aircraft-Sequencing Problem Based on Bee Evolutionary Genetic Algorithm and Clustering Method

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Siliang Wang ; Sch. of Comput. Sci., Sichuan Univ., Chengdu, China

Aircraft-sequencing problem (ASP) is a major issue in air traffic control operations and it is also an NP-hard problem with large-scale and multi-constraint, thus it is hard to find optimal solution efficiently. This paper proposes a hybrid algorithm by means of integrating bee evolutionary genetic algorithm with modified clustering method (named BEGA-CM) for solving ASP. In details, clustering method is suitable to deal with distribution of arrival time window, moreover, we newly define the relative and absolute position in aircraft permutation according to its distribution of cluster, which can help us to construct new crossover and mutation operator and efficiently reduce infeasible permutation and improve convergence speed. Experiments show the hybrid algorithm is able to obtain an optimal landing sequence and landing time rapidly and effectively.

Published in:

Dependable, Autonomic and Secure Computing, 2009. DASC '09. Eighth IEEE International Conference on

Date of Conference:

12-14 Dec. 2009