DocumentCode
554655
Title
Ant colony algorithm for a class of non-differentiable optimization problems
Author
Jiajia He ; Zai-en Hou
Author_Institution
Coll. of Electr. & Inf. Eng., Shaanxi Univ. of Sci. & Technol., Xi´an, China
Volume
5
fYear
2011
fDate
12-14 Aug. 2011
Firstpage
2644
Lastpage
2647
Abstract
There are many methods for solving non-differentiable optimization problems, but most of them are too difficult to realize. In this paper, penalty function method is adopted to transform non-differentiable optimization problems to unconstrained differentiable optimization problems. Then, computational experiments are conducted based on the uncertainty analysis of ant colony algorithm (ACA). Numerical results show that ACA can make such a problem simple and easy to calculate.
Keywords
differentiation; optimisation; ACA; ant colony algorithm; nondifferentiable optimization problems; penalty function method; unconstrained differentiable optimization problems; Accuracy; Algorithm design and analysis; Convergence; Educational institutions; MATLAB; Optimization; ant colony algorithm (ACA); non-differentiable optimization; penalty function;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location
Harbin, Heilongjiang, China
Print_ISBN
978-1-61284-087-1
Type
conf
DOI
10.1109/EMEIT.2011.6023640
Filename
6023640
Link To Document