Improved ant colony optimization algorithm for solving constraint satisfaction problem

被引：0
|
作者：
Zhang, Yong-Gang [1 ,2 ]
Zhang, Si-Bo [1 ,2 ]
Xue, Qiu-Shi [1 ,2 ]
机构：
[1] College of Comprter Science and Technology, Jilin university, Changchun,130012, China
[2] Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education, Changchun,130012, China
来源：
Tongxin Xuebao/Journal on Communications | 2015年 / 36卷 / 05期
关键词：
Arc consistency - Backtracking algorithm - Combinatorial optimization problems - Constraint Solving - Heuristic search - Improved ant colony optimization - New parameters - Parameter adjustments;
D O I：
10.11959/j.issn.1000-436x.2015123
中图分类号：
学科分类号：
摘要：
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 algorithms 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 efficiency 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. ©, 2015, Editorial Board of Journal on Communications. All right reserved.
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