/*
	5-1棋盘覆盖问题（分治法）
	size==1
	dr < tr + s && dc < tc + s
	ChessBoard(tr,tc,dr,dc,s)
	board[tr+s-1][tc+s-1]=t
	ChessBoard(tr,tc,tr+s-1,tc+s-1,s)
	dr < tr + s && dc >= tc + s
	ChessBoard(tr,tc+s,dr,dc,s)
	board[tr+s-1][tc+s]=t
	ChessBoard(tr,tc+s,tr+s-1,tc+s,s)
	dr >= tr + s && dc < tc + s
	ChessBoard(tr+s,tc,dr,dc,s)
	board[tr+s][tc+s-1]=t
	ChessBoard(tr+s,tc,tr+s,tc+s-1,s)
	dr>=tr+s && dc>=tc+s
	ChessBoard(tr+s,tc+s,dr,dc,s)
	board[tr+s][tc+s]=t
	ChessBoard(tr+s,tc+s,tr+s,tc+s,s)

	5-2快速排序（分治法）
	low<high
	low < high && L.r[high] >= pivotkey
	low < high && L.r[low] <= pivotkey
	Partition(L,low,high)
	QSort(L,low,pivotloc-1)
	QSort(L,pivotloc+1,high)

	5-3归并排序(递归法)
	T[low]=R[low]
	MSort(R,S,low,mid)
	MSort(R,S,mid+1,high)
	Merge(S,T,low,mid,high)

	5-4部分背包问题（贪心法）
	A[i].w<=weight
	weight-=A[i].w
	i++
	weight/A[i].w

	5-5最小生成树（普里姆算法）
	min > closedge[i].lowcost && closedge[i].lowcost != 0
	u
	G.arcs[k][j]
	0
	Min(G)
	0
	G.vexs[k]
	G.arcs[k][j]

	5-6求解活动安排问题（贪心法）
	A[i].b>=preend
	flag[i]=true
	preend=A[i].e

	5-7多段图问题（动态规划法）
	arc[i][j] + cost[i] < cost[j]
	cost[j] = arc[i][j] + cost[i]
	path[j]
	cost[n-1]

	5-8最短路径（弗洛伊德算法）
	G.arcs[i][j]
	Path[i][j]=i
	D[i][k] + D[k][j]
	D[i][k]+D[k][j]
	Path[k][j]

	5-9求解图的m着色问题（回溯法）
	a[i][j]==1 && x[i]==x[j]
	count++
	Same(i)
	x[i]=0

	5-10 0/1背包问题（回溯法）
	tw==W && tv>maxv
	j=1;j<=n;j++
	tw+w[i]<=W
	i+1,tw+w[i],tv+v[i],rw-w[i],op
	tw+rw>W
	i+1,tw,tv,rw-w[i],op

	5-11 求解n皇后问题（递归回溯法）
	return false
	return true
	place(i,j)
	queen(i+1,n)


	
	
*/