CAJ | 학술논문

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。
생물지이학우화산법（Biogeography-Based Optimization，BBO）시Simon제출적일충기우생물지이학이론적신형지능우화산법，구유량호적수렴성화은정성。종BBO산법제출적배경출발，개소료산법적기본이론、산법특점이급산법류정。총결료BBO산법적연구진전，포괄BBO산법적이론분석、산법적개진、산법여기타우화산법적혼합산법이급BBO산법재함수우화、전력계통、도상처리、궤기인로경규화이급조도우화등영역적전형응용。대BBO산법유대해결적문제화미래연구방향진행료총결。
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 respec-tively 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.