Novel composition test functions algorithm for numerical optimization

Author

Peng, Fu-ming

Author_Institution

Coll. of Comput. & Software, Nanjing Inst. of Ind. Technol., Nanjing, China

fYear

2011

fDate

27-29 June 2011

Firstpage

3348

Lastpage

3352

Abstract

Since coming out, novel composition test functions have received wide attention from evolutionary computation researchers and have now become the target functions for numerical optimization algorithms. However, its numerical optimization can be transformed into numerical optimization of one-dimensional functions, which significantly reduces optimization level of difficulty. A novel composition test functions algorithm for numerical optimization is proposed, which quotes a muti-population revolutionary algorithm for numerical optimization and uses it to optimize the one-dimensional functions. The experiments proved the algorithm for numerical optimization of novel composition test functions converges to the global optimal solutions.

Keywords

evolutionary computation; optimisation; composition test functions algorithm; evolutionary computation researchers; mutipopulation evolutionary algorithm; numerical optimization algorithms; one-dimensional functions; Computers; Information technology; Optimization; Particle swarm optimization; Software; Software algorithms; dimension reduction; multi-dimensions function; novel composition test functions; numerical optimization; one-dimensional function;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Service System (CSSS), 2011 International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4244-9762-1

Type

conf

DOI

10.1109/CSSS.2011.5974523

Filename

5974523