一、六种算法简介
1、人工蜂群算法 （Artificial Bee Colony Algorithm, ABC）
2、粒子群优化算法PSO
3、鸡群优化算法CSO
4、鱼鹰优化算法OOA
5、蜣螂优化算法DBO
6、红狐优化算法RFO
二、6种算法求解CEC2013
（1）CEC2013简介
参考文献：
[1] Liang J J , Qu B Y , Suganthan P N , et al. Problem Definitions and Evaluation Criteria for the CEC 2013 Special Session on Real-Parameter Optimization. 2013.
（2）部分python代码
from CEC2013.cec2013 import *
import numpy as np
from RFO import RFO
from ABC import ABC
from PSO import PSO
from OOA import OOA
from CSO import CSO
from DBO import DBO
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif']=['Microsoft YaHei']
#主程序
#主程序
function_name =1 #测试函数1-28
SearchAgents_no = 50#种群大小
Max_iter = 100#迭代次数
dim=10#维度 10/30/50/100
lb=-100*np.ones(dim)#下限
ub=100*np.ones(dim)#上限
cec_functions = cec2013(dim,function_name)
fobj=cec_functions.func#目标函数
BestX1,BestF1,curve1 = ABC(SearchAgents_no, Max_iter,lb,ub,dim,fobj)#问题求解
BestX2,BestF2,curve2 = PSO(SearchAgents_no, Max_iter,lb,ub,dim,fobj)#问题求解
BestX3,BestF3,curve3 = OOA(SearchAgents_no, Max_iter,lb,ub,dim,fobj)#问题求解
BestX4,BestF4,curve4 = CSO(SearchAgents_no, Max_iter,lb,ub,dim,fobj)#问题求解
BestX5,BestF5,curve5 = DBO(SearchAgents_no, Max_iter,lb,ub,dim,fobj)#问题求解
BestX6,BestF6,curve6 = DBO(SearchAgents_no, Max_iter,lb,ub,dim,fobj)#问题求解
#画收敛曲线图
Labelstr=['ABC','PSO','OOA','CSO','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(curve6,color=Colorstr[5],linewidth=2,label=Labelstr[5])
plt.xlabel("Iteration")
plt.ylabel("Fitness")
plt.xlim(0,Max_iter)
plt.title("cec2013-F"+str(function_name))
plt.legend()
plt.savefig(str(function_name)+'.png')
plt.show()
#
（3）部分结果
