Suppr超能文献

基于生物地理学优化的马尔可夫模型。

Markov models for biogeography-based optimization.

作者信息

Simon Dan, Ergezer Mehmet, Du Dawei, Rarick Rick

机构信息

Department of Electrical and Computer Engineering, Cleveland State University, Cleveland, OH 44115, USA.

出版信息

IEEE Trans Syst Man Cybern B Cybern. 2011 Feb;41(1):299-306. doi: 10.1109/TSMCB.2010.2051149. Epub 2010 Jun 28.

Abstract

Biogeography-based optimization (BBO) is a population-based evolutionary algorithm that is based on the mathematics of biogeography. Biogeography is the science and study of the geographical distribution of biological organisms. In BBO, problem solutions are analogous to islands, and the sharing of features between solutions is analogous to the migration of species. This paper derives Markov models for BBO with selection, migration, and mutation operators. Our models give the theoretically exact limiting probabilities for each possible population distribution for a given problem. We provide simulation results to confirm the Markov models.

摘要

基于生物地理学的优化算法(BBO)是一种基于生物地理学数学原理的群体进化算法。生物地理学是研究生物有机体地理分布的科学。在BBO中,问题的解类似于岛屿,解之间特征的共享类似于物种的迁移。本文推导了带有选择、迁移和变异算子的BBO的马尔可夫模型。我们的模型给出了给定问题每种可能群体分布的理论精确极限概率。我们提供了仿真结果以证实马尔可夫模型。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验