Document Type
Article
Publication Date
5-1-2014
Publication Title
Information Sciences
Abstract
Biogeography-based optimization (BBO) is an evolutionary optimization algorithm that uses migration to share information among candidate solutions. One limitation of BBO is that it changes only one independent variable at a time in each candidate solution. In this paper, a linearized version of BBO, called LBBO, is proposed to reduce rotational variance. The proposed method is combined with periodic re-initialization and local search operators to obtain an algorithm for global optimization in a continuous search space. Experiments have been conducted on 45 benchmarks from the 2005 and 2011 Congress on Evolutionary Computation, and LBBO performance is compared with the results published in those conferences. The results show that LBBO provides competitive performance with state-of-the-art evolutionary algorithms. In particular, LBBO performs particularly well for certain types of multimodal problems, including high-dimensional real-world problems. Also, LBBO is insensitive to whether or not the solution lies on the search domain boundary, in a wide or narrow basin, and within or outside the initialization domain.
Repository Citation
Simon, Dan; Omran, Mahamed G. H.; and Clerc, Maurice, "Linearized biogeography-based optimization with re-initialization and local search" (2014). Electrical and Computer Engineering Faculty Publications. 317.
https://engagedscholarship.csuohio.edu/enece_facpub/317
DOI
10.1016/j.ins.2013.12.048
Version
Postprint
Publisher's Statement
NOTICE: this is the author’s version of a work that was accepted for publication in Information Sciences. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Information Sciences, 267, , (05-01-2014); 10.1016/j.ins.2013.12.048
Volume
267
