Enhanced social emotional optimisation algorithm with generalised opposition-based learning
Zhaolu Guo, Xuezhi Yue, Kejun Zhang, Changshou Deng, Songhua Liu · International Journal of Computing Science and Mathematics · 2015
Social emotional optimisation algorithm (SEOA) is a newly developed evolutionary algorithm, which exhibits excellent performance for various engineering problems in real–world applications. However, SEOA may easily trap into local optima when solving complex multimodal function optimisation problems. This paper proposes a novel social emotional optimisation algorithm, called GOSEOA, which performs the generalised opposition–based learning (GOBL) strategy with a certain probability during the evolution process. The proposed algorithm uses the generalised opposition–based learning strategy to transform the current population to a generalised opposition–based population. Accordingly, the current population and the generalised opposition–based population are simultaneously considered to increase the probability for finding the global optimum. Experiments conducted on a comprehensive set of benchmark functions indicate that GOSEOA can obtain promising performance on the majority of the test functions.