Theoretical Analysis of Biogeography Based Optimization
- DOI
- 10.2991/mmebc-16.2016.404How to use a DOI?
- Keywords
- meta-heuristic; global optimization; NP hard problem
- Abstract
Since the computation ability of computer improves dramatically, a lot of new meta-heuristic methods arise. All those algorithms are originated from some mechanisms in nature, and are similar in structure and widely used to solve global optimization problems. However, evolutionary algorithm, such as BBO, is lack of strict theory foundation and hard to be analyzed in theory, because it comes from heuristic idea and has complicated random behavior. Therefore, In this paper, we propose a Markov chain model of BBO to analyze the relationship between individual vector and , and prove that a Markov population series in BBO is an absorbing Markov chain. Convergence analysis of BBO is obtained, which is the Markov population series in BBO converge to objective subspace with probability one.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Aijun Zhu AU - Cong Hu AU - Chuanpei Xu AU - Zhi Li PY - 2016/06 DA - 2016/06 TI - Theoretical Analysis of Biogeography Based Optimization BT - Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer PB - Atlantis Press SP - 2011 EP - 2016 SN - 2352-5401 UR - https://doi.org/10.2991/mmebc-16.2016.404 DO - 10.2991/mmebc-16.2016.404 ID - Zhu2016/06 ER -