Title: Enhanced social emotional optimisation algorithm with generalised opposition-based learning

Authors: Zhaolu Guo; Xuezhi Yue; Kejun Zhang; Changshou Deng; Songhua Liu

Addresses: Institute of Medical Informatics and Engineering, School of Science, JiangXi University of Science and Technology, Ganzhou 341000, China ' Institute of Medical Informatics and Engineering, School of Science, JiangXi University of Science and Technology, Ganzhou 341000, China ' College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China ' School of Information Science and Technology, Jiujiang University, Jiujiang 332005, China ' Institute of Medical Informatics and Engineering, School of Science, JiangXi University of Science and Technology, Ganzhou 341000, China

Abstract: 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.

Keywords: evolutionary algorithms; numerical optimisation; social emotional optimisation; generalised opposition-based learning; GOBL; engineering.

DOI: 10.1504/IJCSM.2015.067543

International Journal of Computing Science and Mathematics, 2015 Vol.6 No.1, pp.59 - 68

Received: 11 Jul 2014
Accepted: 20 Aug 2014
Published online: 19 Feb 2015 *

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