基于共生搜索的生物地理学优化算法  

Biogeography-Based Optimization Algorithm on Symbiotic Search

作　　者：朱晓雯 范成礼 卢盈齐[1] 齐铖 李威 Zhu Xiaowen;Fan Chengli;Lu Yingqi;Qi Cheng;Li Wei(Air Force Engineering University,Xi’an 710051,China)

机构地区：[1]空军工程大学,西安710051

出　　处：《航空兵器》2022年第6期40-49,共10页Aero Weaponry

基　　金：国家自然科学基金项目(72001214;62106283)。

摘　　要：为平衡生物地理优化(Biogeography-Based Optimization,BBO)算法在搜索过程中多样性和集约性能力,引入共生生物搜索(Symbiotic Organisms Search,SOS)思想,提出基于共生搜索的生物地理学优化(Symbiotic Biogeography Based Optimization,SBBO)算法。首先,通过共生操作优化初始种群,减小初始种群的随机性。在此基础上,为提高迁移过程对解的多样性的探索能力,避免陷入早熟收敛,提出动态选择迁移算子以及互利迁移算子,并通过余弦自适应因子来平衡两种迁移算子在不同迭代阶段的作用。进一步,提出共栖突变算子,提升算法的种群多样性保持能力。仿真实例表明,该算法可较好地协调局部搜索和全局搜索的能力,能够有效提高求解精度和效率。In order to balance the diversity and intensity of biogeography-based optimization(BBO)algorithm in the search process,the idea of symbiotic organisms search(SOS)is introduced,and the asymbiotic biogeography based optimization(SBBO)algorithm is proposed.Firstly,the initial population is optimized by symbiotic operation to reduce the randomness of the initial population.On this basis,in order to improve the ability to explore the diversity of solutions in the migration process and avoid premature convergence,dynamic selection migration operator and mutually beneficial migration operator are proposed,and the functions of the two migration operators in different iterations are balanced by cosine adaptive factor.Furthermore,a symbiotic mutation operator is proposed to improve the ability of the algorithm to maintain population diversity.Simulation results show that the proposed algorithm can coordinate local search and global search,and improve the accuracy and efficiency.

关 键 词：BBO算法 SOS算法 动态迁移算子 互利迁移算子 共栖变异算子 启发式算法 导弹突防 武器目标分配 

分 类 号：TJ760[兵器科学与技术—武器系统与运用工程]