Title :
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
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;
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
DOI :
10.1109/CSO.2011.245
