一、算法介绍
吸血水蛭优化器（Blood-Sucking Leech Optimizer，BSLO）是2024年提出的一种智能优化算法，该算法模拟了水蛭的探索、定向水蛭的利用、定向水蛭的切换机制、无方向水蛭的搜索策略和重新跟踪策略。
参考文献：
1\]Bai, Jianfu, et al. "Blood-Sucking Leech Optimizer." Advances in Engineering Software, vol. 195, Elsevier BV, Sept. 2024, p. 103696, doi:[10.1016/j.advengsoft.2024.103696](https://doi.org/10.1016/j.advengsoft.2024.103696 "10.1016/j.advengsoft.2024.103696") ### 二、23个函数简介  [参考文献](https://so.csdn.net/so/search?q=%E5%8F%82%E8%80%83%E6%96%87%E7%8C%AE&spm=1001.2101.3001.7020 "参考文献")： \[1\] Yao X, Liu Y, [Lin](https://so.csdn.net/so/search?q=Lin&spm=1001.2101.3001.7020 "Lin") G M. Evolutionary programming made faster\[J\]. IEEE transactions on evolutionary computation, 1999, 3(2):82-102. ### 三、部分代码 ``` close all ; clear clc Npop=30; Function_name='F1'; % Name of the test function that can be from F1 to F23 ( Tmax=300; [lb,ub,dim,fobj]=Get_Functions_details(Function_name); [Best_fit,Best_pos,Convergence_curve]=(Npop,Tmax,lb,ub,dim,fobj); figure('Position',[100 100 660 290]) %Draw search space subplot(1,2,1); func_plot(Function_name); title('Parameter space') xlabel('x_1'); ylabel('x_2'); zlabel([Function_name,'( x_1 , x_2 )']) %Draw objective space subplot(1,2,2); semilogy(Convergence_curve,'Color','r','linewidth',3) title('Search space') xlabel('Iteration'); ylabel('Best score obtained so far'); axis tight grid on box on legend('') saveas(gca,[Function_name '.jpg']); display(['The best solution is ', num2str(Best_pos)]); display(['The best fitness value is ', num2str(Best_fit)]); ``` ### 四、部分结果          ### 五、完整MATLAB代码 