Binary and Continuous Ant Colony Algorithms Research for Solving Continuous Global Optimization Problem

摘要：

The paper presents two formalizations,called binary(BACO)and continuous(CACO)ant colony optimization,for the design of ant colony algorithm(ACOA)to solve continuous global optimization problem.With different coding methods and ACOA decision policies,BACO and CACO have distinct characters.In this paper,BACO adopts disturbance factor and CACO uses adaptive search steps to avoid premature convergence,and both of them combine with dynamic evaporation factor to find the best solution,then a convergence proof is presented.The differences of performance between them are compared in the optimization problem of multidimension and multi-minima continuous function,especially with the adaptive genetic algorithm(AGA),and experimental result shows that CACO is effective as it outperforms BACO and AGA.

作者: ZHANG Qin WANG Xiong-hai

作者单位: Dept.of Electrical engineering,Zhejiang Univ.,Hangzhou 310027,China

会议类型: 国际会议

会议名称: 第一届智能网络与智能系统国际会议(ICINIS 2008)(The First International Conference on Intelligent Networks and Intelligent Systems)

会议地点: 武汉

会议语种:英文

在线出版日期: 2008-11-01（万方平台首次上网日期，不代表论文的发表时间）