人工鱼群算法求函数的最大值

# -*- coding: utf-8 -*- import random import math class ASFA: #constructor def __init__(self): print ('This is the instance of ASFA!') #鱼群初始化 def AF_init(self,Nfish,lb_ub): X = [] lb = lb_ub[0] ub = lb_ub[1] for k in range(Nfish): X.append(lb + (ub-lb)*random.random()) return X def AF_dist(self,xi,X): #计算第i条人工鱼与所有鱼的位置，包括本身。 #input:xi(第i条人工鱼的位置), x(所有鱼的当前位置) D = [] Nfish = len(X) for i in range(Nfish): D.append(abs(X[xi]-X[i])) return D def AF_foodconsistence(self,xi): yi = xi*math.sin(10*math.pi*xi)+2 #yi = math.sin(10*math.pi*xi) return yi def AF_prey(self,X,i,lb_ub,try_num,visual,step,lastY): # 只针对一条人工鱼而不是鱼群 # input: i, X, try_num # output: xnext # Nfish = len(X) y = lastY[i] for k in range(try_num): #随机选择一个状态,并计算食物浓度 #for j in range(Nfish): xv = X[i]+(2*random.random()-1)*visual yv = self.AF_foodconsistence(xv) #xi向xv的方向移动一步 if yv > y: xnext = X[i] + random.random()*step*(xv-X[i])/abs(xv-X[i]) if xnext > lb_ub[1]: xnext = lb_ub[1] elif xnext < lb_ub[0]: xnext = lb_ub[0] return xnext #break; #如果尝试不成功就随机移动一步 print("try unsuccessfully!!!") xv = X[i]+(2*random.random()-1)*visual xnext = xv if xnext > lb_ub[1]: xnext = lb_ub[1] elif xnext < lb_ub[0]: xnext = lb_ub[0] return xnext def AF_swarm(self,X,i,lb_ub,try_num,visual,step,deta,lastY): D = self.AF_dist(i,X) index = [] Xc = 0 #Yc = 0 for k in range(len(D)): if D[k] < visual: index.append(k) nf = len(index) if nf > 0: for j in range(nf): Xc = Xc + X[index[j]] Xc = Xc/nf Yc = self.AF_foodconsistence(Xc) Yi = lastY[i] if Yc/nf > deta*Yi: Xnext = X[i] + random.random()*step*(Xc-X[i])/abs(Xc-X[i]) if Xnext > lb_ub[1]: Xnext = lb_ub[1] elif Xnext < lb_ub[0]: Xnext = lb_ub[0] else: Xnext = self.AF_prey(X,i,lb_ub,try_num,visual,step,lastY) else: Xnext = self.AF_prey(X,i,lb_ub,try_num,visual,step,lastY) return Xnext # -*- coding: utf-8 -*-