Central force optimization algorithm based on differential evolution operator mutation
Abstract：In order to avoid obtaining local optimal solution of central force optimization algorithm, strengthen the ability of searching, a new algorithm is proposed based on differential evolution algorithm. According to the characteristics of differential evolution algorithm, differential evolution operator mutation is introduced to mutate the component of particle and reduce the possibility of trapping in the local optimum and to improve the convergence speed of global searching. Using 5 classic benchmark functions to test, simulation results show that, compared with several other algorithms, the precision of the new algorithm is remarkably improved, therefore the effectiveness and feasibility of the algorithm is proved correct.
Keywords：central force optimization algorithmparticle swarm optimization algorithmdifferential evolutionglobal optimization
Publication Date：2012-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 197-203 )