Improved ant colony optimization algorithm for solving constraint satisfaction problem - HANGYong-gang Z; HANGSi-bo Z; UEQiu-shi X (Tongxin xuebao)
The traditional backtracking algorithm was less efficient on solving large-scale constraint satisfaction problem,and more difficult to be solved within a reasonable time.In order to overcome this problem,many incompleteness algo-rithms based on heuristic search have been proposed.Two improvements based on ant colony optimization meta-heuristic constraint solving algorithm were presented:First,arc consistency checks was done to preprocess before exploring the search space,Second,a new parameter setting scheme was proposed for ant colony optimization to improve the effi-ciency of the search.Finally,the improved algorithm is applied to solve random problems and combinatorial optimization problems.The results of the experiment have showed its superiority.