Directed differential evolution based on directional derivative for numerical optimization problems

Author

Zhang, Jun ; Luo, Wenjian

Author_Institution

Sch. of Comput. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei, China

fYear

2011

fDate

5-8 Dec. 2011

Firstpage

340

Lastpage

345

Abstract

Differential Evolution is one kind of Evolutionary Algorithms, which has been successfully applied to solve many optimization problems. In this paper, a directed differential mutation (DDM), which utilizes the directional derivative to decide a suitable search direction and a proper mutation step size, is proposed. It is merged into the classical DE to form a new algorithm, named directed differential evolution (DDE). The performance of the DDE is tested on 23 classical problems for numerical optimization. The experimental results demonstrate that the performance of the DDE outperforms the classical DE on most functions.

Keywords

evolutionary computation; optimisation; directed differential evolution; directed differential mutation; directional derivative; evolutionary algorithms; numerical optimization; Algorithms; Equations; Hybrid intelligent systems; Maintenance engineering; Optimization; Programming; Vectors; differential evolution; directional derivative; numerical optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Hybrid Intelligent Systems (HIS), 2011 11th International Conference on

Conference_Location

Melacca

Print_ISBN

978-1-4577-2151-9

Type

conf

DOI

10.1109/HIS.2011.6122129

Filename

6122129