Title :
A Fast Opposition-Based Differential Evolution with Cauchy Mutation
Author :
Yong Wu ; Bin Zhao ; Jinglei Guo
Author_Institution :
Sch. of Autom., Wuhan Univ. of Technol., Wuhan, China
Abstract :
Opposition-based Differential Evolution (ODE) has been proved to be an effective method to Differential Evolution (DE) in solving many optimization functions, and it´s faster and more robust convergence than classical DE. In this paper, a fast ODE algorithm (FODE), using a local search method with Cauchy mutation is proposed. The simulation experiments are conducted on a comprehensive set of 10 complex benchmark functions. Compared with ODE, FODE is faster and more robust.
Keywords :
evolutionary computation; search problems; DE; cauchy mutation; convergence; fast ODE algorithm; fast opposition-based differential evolution; local search method; Acceleration; Algorithm design and analysis; Benchmark testing; Convergence; Optimization; Sociology; Statistics; Opposition-based Differential Evolution (ODE); cauchy mutation; convergence; local search;
Conference_Titel :
Intelligent Systems (GCIS), 2012 Third Global Congress on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4673-3072-5
DOI :
10.1109/GCIS.2012.91
