학술논문
Enhanced social emotional optimisation algorithm with elite multi-parent crossover
Document Type
Article
Source
International Journal of Computing Science and Mathematics; 2016, Vol. 7 Issue: 6 p568-574, 7p
Subject
Language
ISSN
17525055; 17525063
Abstract
Social emotional optimisation algorithm (SEOA) has been successfully applied in a variety of real-world applications. However, it may suffer from slow convergence rate when solving complex optimisation problems. In order to improve the performance of SEOA on complex optimisation problems, in this paper, an enhanced social emotional optimisation algorithm with elite multi-parent crossover (MCSEOA) is proposed. In MCSEOA, it employs the elite multi-parent crossover operator to exploit the neighbourhood solutions of the current population. The numerical experiments are conducted on 13 classical test functions. Comparison results demonstrate that MCSEOA can significantly improve the performance of the traditional SEOA.