一、六種算法簡介

1、蜣螂優化算法DBO

2、紅狐優化算法RFO

3、鯨魚優化算法WOA

4、灰狼優化算法GWO

5、粒子群優化算法PSO

6、遺傳算法GA

二、6種算法求解23個函數

（1）23個函數簡介

參考文獻：

[1] Yao X, Liu Y, Lin G M. Evolutionary programming made faster[J]. IEEE transactions on evolutionary computation, 1999, 3(2):82-102.

（2）部分python代碼

from FunInfo import Get_Functions_details
from WOA import WOA
from GWO import GWO
from PSO import PSO
from GA import GA
from DBO import DBO
from RFO import RFO
import matplotlib.pyplot as plt
from func_plot import func_plot
plt.rcParams['font.sans-serif']=['Microsoft YaHei']
#主程序
function_name =12 #測試函數1-23
SearchAgents_no = 50#種群大小
Max_iter = 100#迭代次數
lb,ub,dim,fobj=Get_Functions_details(function_name)#獲取問題信息
BestX1,BestF1,curve1 = WOA(SearchAgents_no, Max_iter,lb,ub,dim,fobj)#問題求解
BestX2,BestF2,curve2 = GWO(SearchAgents_no, Max_iter,lb,ub,dim,fobj)#問題求解
BestX3,BestF3,curve3 = PSO(SearchAgents_no, Max_iter,lb,ub,dim,fobj)#問題求解
BestX4,BestF4,curve4 = GA(SearchAgents_no, Max_iter,lb,ub,dim,fobj)#問題求解
BestX5,BestF5,curve5 = DBO(SearchAgents_no, Max_iter,lb,ub,dim,fobj)#問題求解
BestX6,BestF6,curve6 = RFO(SearchAgents_no, Max_iter,lb,ub,dim,fobj)#問題求解
#畫函數圖
func_plot(lb,ub,dim,fobj,function_name)#畫函數圖
#畫收斂曲線圖
Labelstr=['WOA','GWO','PSO','GA','DBO','RFO']
Colorstr=['r','g','b','k','c','m']
if BestF1>0:plt.semilogy(curve1,color=Colorstr[0],linewidth=2,label=Labelstr[0])plt.semilogy(curve2,color=Colorstr[1],linewidth=2,label=Labelstr[1])plt.semilogy(curve3,color=Colorstr[2],linewidth=2,label=Labelstr[2])plt.semilogy(curve4,color=Colorstr[3],linewidth=2,label=Labelstr[3])plt.semilogy(curve5,color=Colorstr[4],linewidth=2,label=Labelstr[4])plt.semilogy(curve6,color=Colorstr[5],linewidth=2,label=Labelstr[5])
else:plt.plot(curve1,color=Colorstr[0],linewidth=2,label=Labelstr[0])plt.plot(curve2,color=Colorstr[1],linewidth=2,label=Labelstr[1])plt.plot(curve3,color=Colorstr[2],linewidth=2,label=Labelstr[2])plt.plot(curve4,color=Colorstr[3],linewidth=2,label=Labelstr[3])plt.plot(curve5,color=Colorstr[4],linewidth=2,label=Labelstr[4])plt.plot(curve5,color=Colorstr[5],linewidth=2,label=Labelstr[5])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()
#

（3）部分結果

三、完整python代碼