State Transition Strategy Analysis of Ant Colony Algorithms

Author

Liu, Liqiang ; Dai, Yuntao ; Tao, Chunyan

Author_Institution

Coll. of Autom., Harbin Eng. Univ., Harbin, China

fYear

2011

fDate

15-19 April 2011

Firstpage

969

Lastpage

973

Abstract

Based on the analysis of ant colony algorithm random-proportional rule and pseudo-random-proportional rule, general expressions of state transition strategy is proposed in this paper and the concept of selection function, selection probability and selection intensity are given. Selection functions of power function relation, exponential function relation and sorting strategy are designed, and the influence of different selection functions on performance of ant colony algorithm is analyzed theoretically. Under different state transition strategies, the convergence, stability and optimization performance of ant colony algorithm are discussed by simulation results.

Keywords

convergence of numerical methods; optimisation; probability; ant colony algorithm; convergence stability; exponential function relation; optimization; pseudorandom proportional rule; random proportional rule; selection function; selection intensity; selection probability; sorting strategy; state transition strategy; Algorithm design and analysis; Convergence; Genetic expression; Heuristic algorithms; Optimization; Simulation; Stability analysis; ant colony algorithms; selection function; state transition strategy;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on

Conference_Location

Yunnan

Print_ISBN

978-1-4244-9712-6

Electronic_ISBN

978-0-7695-4335-2

Type

conf

DOI

10.1109/CSO.2011.245

Filename

5957819