Novel method based on ant colony opti mization for solving ill-conditioned linear systems of equations

被引：4

作者：

段海滨

王道波

朱家强

机构：

[1] School of Automation Science and Electrical Engineering

[2] Beijing Univ of Aeronautics and Astronautics

[3] Coll of Automation Engineering

[4] Nanjing Univ of Aeronautics and Astronautics

[5] State Key Laboratory of Intelligent Technology and Systems

[6] Tsinghua Univ Beijing

[7] P R China

[8] Nanjing

[9] Beijing

来源：

JournalofSystemsEngineeringandElectronics | 2005年 / 03期

关键词：

ill conditioned linear systems of equations; ant colony optimization; condition number; optimization;

D O I：

暂无

中图分类号：

TP11 [自动化系统理论];

学科分类号：

0711 ; 071102 ; 0811 ; 081101 ; 081103 ;

摘要：

A novel method based on ant colony optimization (ACO), algorithm for solving the ill conditioned linear systems of equations is proposed. ACO is a parallelized bionic optimization algorithm which is inspired from the behavior of real ants. ACO algorithm is first introduced, a kind of positive feedback mechanism is adopted in ACO. Then, the solution problem of linear systems of equations was reformulated as an unconstrained optimization problem for solution by an ACO algorithm. Finally, the ACO with other traditional methods is applied to solve a kind of multi dimensional Hilbert ill conditioned linear equations. The numerical results demonstrate that ACO is effective, robust and recommendable in solving ill conditioned linear systems of equations.

引用

页码：606 / 610

页数：5