A Dynamic Ant Colony Algorithm with Disaster

Author

Wei, Ping ; Xiong, Weiqing

Author_Institution

Inst. of Comput. Sci. & Technol., Ningbo Univ.

Volume

1

fYear

0

fDate

0-0 0

Firstpage

3076

Lastpage

3080

Abstract

Despite the numerous applications of ant colony algorithm in the optimization computation, there still exist, in the large-scale solution of problems, some shortcomings such as the long running time and the early convergence. This paper, on the basis of basic ant system algorithm, tries to improve the algorithm by means of the introduction of disaster, two-way search, 2-opt method, subsection save, dynamic innovation of such factor as pheromone. Some instances in TSPLIB have achieved or even exceeded the best solution ever recorded, which indicates that the improvement is excellent

Keywords

convergence; evolutionary computation; particle swarm optimisation; search problems; travelling salesman problems; 2-opt method; TSPLIB; ant system algorithm; disaster; dynamic ant colony algorithm; dynamic innovation; optimization computation; simulated evolutionary algorithm; subsection save; traveling salesman problem; two-way search; Ant colony optimization; Application software; Automation; Computer science; Evolutionary computation; Heuristic algorithms; Intelligent control; Large-scale systems; Technological innovation; Traveling salesman problems; Ant System Algorithm; Simulated Evolutionary Algorithm; Traveling Salesman Problem; disaster;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712932

Filename

1712932