面向对象编程之Python实现遗传算法三

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import random import math ########################################################################### class Point: size=0 xmin=0.0 xmax=0.0   def __init__(self): self.x=[] for i in range(Point.size): if(random.random()>0.5): self.x.append(1) else: self.x.append(0)
def decode(self): vx=0 for i in range(Point.size): vx=vx+self.x[i]*(2**(Point.size-i-1)) vx=Point.xmin+vx*(Point.xmax-Point.xmin)/(2**Point.size-1.0) return vx
def getFitness(self): vy=self.decode() y=vy*math.sin(vy*10*math.pi)+2.0 return y
def show(self): print(self.x,self.decode(),self.getFitness()) ################################################################ class Tools: def __init__(self): self.temp=Point() def cross(self,a,b,ab,ba): pos=random.randint(0,Point.size-1) for i in range(pos): ab.x[i]=a.x[i] ba.x[i]=b.x[i] for i in range(pos,Point.size-1): ba.x[i]=a.x[i] ab.x[i]=b.x[i]
def copy(self,a,b): for i in range(Point.size): b.x[i]=a.x[i]
def mutA(self,a): pos=random.randint(0,Point.size-1) a.x[pos]=(a.x[pos]+1)%2
def getBestPos(self,array): pos=0 self.copy(array[pos],self.temp) for i in range(len(array)): if(self.temp.getFitness()<array[i].getFitness()): self.copy(array[i],self.temp) pos=i return pos
def getBadPos(self,array): pos=0 self.copy(array[pos],self.temp) for i in range(len(array)): if(self.temp.getFitness()>array[i].getFitness()): self.copy(array[i],self.temp) pos=i return pos #end class Tools ########################################################################## class GA: t=Tools() def __init__(self,size,T): self.size=size self.obj=[] self.nextobj=[] self.sump=[] self.temp=Point()
for i in range(self.size): self.obj.append(Point()) self.nextobj.append(Point()) self.sump.append(0.0)
def cal(self): sum=0 for i in range(self.size): self.sump[i]=self.obj[i].getFitness() sum=sum+self.sump[i] j=0 while(j<self.size): if(j>0): self.sump[j]=self.sump[j]+self.sump[j-1] j=j+1 j=0 while(j<self.size): self.sump[j]=self.sump[j]/sum j=j+1
def select(self): for i in range(self.size): if(random.random()<self.sump[i]): pos=i break return pos
def doAll(self): self.cal() bestPos=t.getBestPos(self.obj) t.copy(self.obj[bestPos],self.temp)
i=0 while(i<len(self.obj)/2): m=self.select() n=self.select() if(random.random()<0.85): t.cross(self.obj[m],self.obj[n],self.nextobj[2*i],self.nextobj[2*i+1]) else: t.copy(self.obj[n],self.nextobj[2*i]) t.copy(self.obj[m],self.nextobj[2*i+1]) i=i+1
i=0 while(i<len(self.obj)): if(random.random()>0.95): t.mutA(self.nextobj[i]) i=i+1 badpos=t.getBadPos(self.nextobj) t.copy(self.temp,self.nextobj[badpos])
i=0 while(i<len(self.obj)): t.copy(self.nextobj[i],self.obj[i]) i=i+1 #end GA
Point.size=22 Point.xmax=2.0 Point.xmin=-1.0
t=Tools() s=GA(40,t) i=0
while(i<500): s.doAll() i=i+1
bestPos=t.getBestPos(s.obj) s.obj[bestPos].show()

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