Computer Engineering and Applications ›› 2015, Vol. 51 ›› Issue (3): 12-17.

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Review on biogeography-based optimization algorithm and applications

ZHANG Guohui1, NIE Li2, ZHANG Liping3   

  1. 1.School of Management Science and Engineering, Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou 450015, China
    2.School of Mechanical & Electronic Engineering, Shanghai Second Polytechnic University, Shanghai 201209, China
    3.School of Machinery and Automation, Wuhan University of Science & Technology, Wuhan 430081, China
  • Online:2015-02-01 Published:2015-01-28

生物地理学优化算法理论及其应用研究综述

张国辉1,聂  黎2,张利平3   

  1. 1.郑州航空工业管理学院 管理科学与工程学院,郑州 450015
    2.上海第二工业大学 机电工程学院,上海 201209
    3.武汉科技大学 机械自动化学院,武汉 430081

Abstract: Simon Dan proposes a new type of intelligence optimization algorithm based on the biogeography theory, named the Biogeography-Based Optimization algorithm(BBO), and it has good ability of convergence and stability. From the proposed background of the BBO algorithm, the basic theory, characteristics and the steps of the BBO algorithm are discussed. The research progress is summarized, including the theory analysis, the improvement of BBO algorithm, and the hybrid algorithm to other optimization algorithms. And several typical application areas of BBO algorithm are surveyed respectively including function optimization, power system, image processing, robot path planning, and scheduling optimization. The problems to be solved and future research directions of BBO algorithm are summarized.

Key words: biogeography-based optimization algorithm, evolutionary algorithm, intelligence optimization algorithm, migration operator

摘要: 生物地理学优化算法(Biogeography-Based Optimization,BBO)是Simon提出的一种基于生物地理学理论的新型智能优化算法,具有良好的收敛性和稳定性。从BBO算法提出的背景出发,介绍了算法的基本理论、算法特点以及算法流程。总结了BBO算法的研究进展,包括BBO算法的理论分析、算法的改进、算法与其他优化算法的混合算法以及BBO算法在函数优化、电力系统、图像处理、机器人路径规划以及调度优化等领域的典型应用。对BBO算法有待解决的问题和未来研究方向进行了总结。

关键词: 生物地理学优化算法, 进化算法, 智能优化算法, 迁移操作