caa a22 4500 60546894X CHVBK 20210128100319.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s00500-014-1370-1 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1370-1 Drift analysis of mutation operations for biogeography-based optimization [Elektronische Daten] [Weian Guo, Lei Wang, Shuzhi Ge, Hongliang Ren, Yanfen Mao] As an essential factor of evolutionary algorithms (EAs), mutation operator plays an important role in exploring the search space, maintaining the diversity of individuals and breaking away local optimums. In most standard evolutionary algorithms, the mutation operator is independent from the recombination operator. Nevertheless, in biogeography-based optimization (BBO), the mutation operator is affected not only by predefined constants but also by recombination models, namely the migration operator. However to date, the relationship between the mutation and migration has never been investigated. To reveal the relationship and evaluate the mutation models, we utilize drift analysis to investigate the expected first hitting time of BBO with different migration models. The analysis compares three different kinds of mutation models in a mathematical way and the conclusion is helpful for designing migration models of BBO. The simulation results are also in agreement with our analysis. Springer-Verlag Berlin Heidelberg, 2014 Evolutionary algorithm nationallicence Mutation operator nationallicence Migration operator nationallicence Biogeography-based optimization nationallicence Drift analysis nationallicence Expected first hitting time nationallicence Guo Weian Sino-German College of Applied Science, Tongji University, 201804, Shanghai, China aut Wang Lei Shanghai Key Laboratory of Financial Information Technology, Shanghai University of Finance and Economics, 200433, Shanghai, China aut Ge Shuzhi Social Robotics Laboratory, Interactive Digital Media Institute, Electrical and Computer Engineering, National University of Singapore, 119077, Singapore, Singapore aut Ren Hongliang Department of Biomedical Engineering, National University of Singapore, 117575, Singapore, Singapore aut Mao Yanfen Sino-German College of Applied Science, Tongji University, 201804, Shanghai, China aut Soft Computing Springer Berlin Heidelberg 19/7(2015-07-01), 1881-1892 1432-7643 19:7<1881 2015 19 500 https://doi.org/10.1007/s00500-014-1370-1 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1370-1 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Guo Weian Sino-German College of Applied Science, Tongji University, 201804, Shanghai, China aut NATIONALLICENCE 700 1- Wang Lei Shanghai Key Laboratory of Financial Information Technology, Shanghai University of Finance and Economics, 200433, Shanghai, China aut NATIONALLICENCE 700 1- Ge Shuzhi Social Robotics Laboratory, Interactive Digital Media Institute, Electrical and Computer Engineering, National University of Singapore, 119077, Singapore, Singapore aut NATIONALLICENCE 700 1- Ren Hongliang Department of Biomedical Engineering, National University of Singapore, 117575, Singapore, Singapore aut NATIONALLICENCE 700 1- Mao Yanfen Sino-German College of Applied Science, Tongji University, 201804, Shanghai, China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/7(2015-07-01), 1881-1892 1432-7643 19:7<1881 2015 19 500