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
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;
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
DOI :
10.1109/EMEIT.2011.6023640
