Title :
An Intensified Ant Colony System Algorithm Applied to a Class of Air Vehicle Route Planning Problem
Author :
Luo, Xiong ; Sun, Zengqi ; Fan, Xiaoping
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ. Beijing
Abstract :
Air vehicle route planning (AVRP) plays a very important role in the system of task planning. A class of extended AVRP problem was discussed. At present, there are some advanced algorithms used to solve this optimal problem. In order to improve the search efficiency of current algorithms, the intensified ant colony system algorithm was proposed with the help of the pre-processing for this particular problem. Meanwhile, based on the functional analysis, the convergence of the proposed algorithm was also analyzed. The optimal problem was solved with numerical analysis and computations. By comparing the proposed algorithm with existing hybrid evolutionary computation simulated annealing algorithm, the simulation results show that the accuracy and efficiency of the algorithm
Keywords :
aircraft navigation; artificial life; optimisation; path planning; air vehicle route planning problem; ant colony optimization; functional analysis; intensified ant colony system algorithm; numerical analysis; task planning; Ant colony optimization; Automotive engineering; Computational modeling; Computer science; Costs; Information science; Simulated annealing; Sun; Technology planning; Vehicles; Air vehicle route planning; ant colony optimization; ant colony system;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1713033