计算机科学 ›› 2010, Vol. 37 ›› Issue (7): 34-38.

• 综述 • 上一篇    下一篇

生物地理学优化算法综述

王存睿,王楠楠,段晓东,张庆灵   

  1. (大连民族学院非线性信息技术研究所 大连116600);(东北大学系统科学研究所 沈阳110004)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金(60573124),辽宁省自然科学基金(20072197),高校科研项目计划(20060146)资助。

Survey of Biogeography-based Optimization

WANG Cun-rui,WANG Nan-nan,DUAN Xiao-dong,ZHANG Qing-ling   

  • Online:2018-12-01 Published:2018-12-01

摘要: 生物地理学(Biogeography)是一门研究自然界种群迁移机制的科学,Dan Simon用生物地理学的方法和机制来解决工程优化问题,提出了生物地理学优化算法(BBO,Biogcography-Bascd Optimization)。生物地理学优化算法以其独特的搜索机制和较好的性能在智能优化算法领域得到了广泛的关注。对生物地理学优化算法的设计原理、迁徒模型、算法流程及相应迁移和突变操作进行了综述。通过BBO算法在14个基准函数下与传统算法,如遗传算法、蚁群算法和粒子群等优化算法的性能比较,表明生物地理学优化算法是有效的。论述了算法与传统优化算法之间的差异以及BBO算法有待解决的问题。

关键词: 优化算法,生物地理学优化算法,智能优化

Abstract: Biogeography is the study of the geographical distribution of biological organisms, Prof. Dan Simon took the mechanism to resolve engineering problems,and proposed a new optimization algorithm named Biogeography-Based Optimization (BBO).BBO algorithm has a wide attention by its unique search mechanism and good performance. We over-viewed the BBO's natural mechanism, the math model of BBO migration, the progress of BBO, migration and mutation operation of BBO. We listed the results of BBO tests on a set of 14 standard benchmarks and compared it with UA,ACO, and PSO etc to prove its good performance. This paper also discussed the difference of BBO with traditional optimization algorithms and the future problems of BBO.

Key words: Optimization algorithm, Biogeography-based optimization, Intelligence optimization

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