改进型鳟海鞘算法(SSALEO)由Mohammed Qaraad等人于2022年提出。
参考文献:M. Qaraad, S. Amjad, N. K. Hussein, S. Mirjalili, N. B. Halima and M. A. Elhosseini, "Comparing SSALEO as a Scalable Large Scale Global Optimization Algorithm to High-Performance Algorithms for Real-World Constrained Optimization Benchmark," in IEEE Access, vol. 10, pp. 95658-95700, 2022, doi: 10.1109/ACCESS.2022.3202894.
23个测试函数简介
测试集:23组基本测试函数简介及图像(提供python代码)_IT猿手的博客-CSDN博客
部分代码
from FunInfo import Get_Functions_details from SSALEO import SSALEO import matplotlib.pyplot as plt plt.rcParams['font.sans-serif']=['Microsoft YaHei'] #主程序 function_name =13 #测试函数1-23 SearchAgents_no = 50#种群大小 Max_iter = 100#迭代次数 lb,ub,dim,fobj=Get_Functions_details(function_name)#获取问题信息 BestX,BestF,curve = SSALEO(SearchAgents_no, Max_iter,lb,ub,dim,fobj)#问题求解 #画收敛曲线图 if BestF>0: ? ? plt.semilogy(curve,color='r',linewidth=2,label='SSALEO') else: ? ? plt.plot(curve,color='r',linewidth=2,label='SSALEO') plt.xlabel("Iteration") plt.ylabel("Fitness") plt.xlim(0,Max_iter) plt.title("F"+str(function_name)) plt.legend() plt.savefig(str(function_name)+'.png') plt.show() print('\nThe best solution is:\n'+str(BestX)) print('\nThe best optimal value of the objective funciton is:\n'+str(BestF))
部分结果