接上一篇，同样的01背包问题，上一篇采用动态规划的方法，现在用回溯法解决。回溯法采用深度优先策略搜索问题的解，不多说，代码如下：

bestV=0
curW=0
curV=0
bestx=None

def backtrack(i):
	global bestV,curW,curV,x,bestx
	if i>=n:
		if bestV<curV:
			bestV=curV
			bestx=x[:]
	else:
		if curW+w[i]<=c:
			x[i]=True
			curW+=w[i]
			curV+=v[i]
			backtrack(i+1)
			curW-=w[i]
			curV-=v[i]
		x[i]=False
		backtrack(i+1)
	

if __name__=='__main__':
	n=5
	c=10
	w=[2,2,6,5,4]
	v=[6,3,5,4,6]
	x=[False for i in range(n)]
	backtrack(0)
	print(bestV)
	print(bestx)

转载请注明：转自http://blog.csdn.net/littlethunder/article/details/26621427