一、CEC2017简介
参考文献：
1\]Awad, N. H., Ali, M. Z., Liang, J. J., Qu, B. Y., \& Suganthan, P. N. (2016). "**Problem definitions and evaluation criteria for the CEC2017 special session and competition on single objective real-parameter numerical optimization**," Technical Report. Nanyang Technological University, Singapore. ### 二、蜣螂优化算法DBO求解CEC2017 #### （1）部分Python代码 ``` from DBO import DBO import matplotlib.pyplot as plt import numpy as np import cec2017.functions as functions #主程序 function_name =6 #测试函数 1-29 SearchAgents_no = 50#种群大小 Max_iter = 100#最大迭代次数 dim=30;#维度只能是 10/30/50/100 lb = -100*np.ones(dim)#下界 ub = 100*np.ones(dim)#上界 fobj= functions.all_functions[function_name-1] BestX,BestF,curve = DBO(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=3,label='DBO') else: plt.plot(curve,color='r',linewidth=3,label='DBO') plt.xlabel("Iteration") plt.ylabel("Fitness") plt.xlim(0,Max_iter) plt.title("CEC2017-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)) ```  #### （2）部分结果       ### 三、完整Python代码 