An Improved Hybridizing Biogeographyo-Based Optimization with Differential Evolution for Global Numerical Optimization

摘要：

　　Biogeography-based optimization (BBO) is a new biogeography inspired algorithm.It mainly uses the biogeography-based migration operator to share the information among solution.Differential evolution (DE) is a fast and robust evolutionary algorithm for global optimization.In this paper, we applied an improved hybridization of BBO with DE approach, namely BBO/DE/GEN, for the global numerical optimization problems.BBO/DE/GEN combines the exploitation of BBO with the exploration of DE effectively and the migration operators of BBO were modified based on number of iteration to improve performance.And hence it can generate the promising candidate solutions.To verify the performance of our proposed BBO/DE/GEN, 6 benchmark functions with a wide range of dimensions and diverse complexities are employed.Experimental results indicate that our approach is effective and efficient.Compared with BBO and BBO/DE approaches, BBO/DE/GEN performs better, or at least comparably, in terms of the quality of the final solutions and the convergence rate.

关键词： Biogeography-Based Optimization Differential evolution Global numerical optimization

作者: Si-ling Feng Qing-xin Zhu Xiu-jun Gong Sheng Zhong

作者单位: School of Computer Science & Engineering,University of Electronic Science and Technology of China,Ch School of Computer Science & Engineering,University of Electronic Science and Technology of China,Ch School of Computer Science and Technology,Tianjin University,Tianjin,China College of Information Science & Technology,Hainan University,Haikou,China

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Science and Social Research (2013年第二届科学与社会研究国际会议)(ICSSR2013)

会议地点: 北京

会议语种:英文

页码: 309-312

在线出版日期: 2013-07-13（万方平台首次上网日期，不代表论文的发表时间）