dynamic programming (ii)

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Tim Au Yeung

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Dynamic Programming (II). Tim Au Yeung. Tree DP. Dynamic Programming on Tree “always” from leaves to root Children node pass information to parent, obtain solution from root Unrooted tree Choose any node to be the root Rooted tree: Use specific root. Tree DP. Build tree DFS/BFS - PowerPoint PPT Presentation

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Page 1: Dynamic Programming (II)

Tim Au Yeung

Page 2: Dynamic Programming (II)

Dynamic Programming on Tree “always” from leaves to root Children node pass information to parent,

obtain solution from root

Unrooted tree Choose any node to be the root

Rooted tree: Use specific root

Page 3: Dynamic Programming (II)

Build tree DFS/BFS Set base case on leaves Backtrack and update the optimal value

for each node Obtain solution at root

Page 4: Dynamic Programming (II)

http://poj.org/problem?id=1655

Given a tree with N nodes Define Balance[i] as the max size of

subtrees after removing node i Output: x

where Balance[x] is min

Page 5: Dynamic Programming (II)

PreProcess DFS and DP: get num[i], the number of nodes

in subtree rooted at i Calculate Balance[i]

Page 6: Dynamic Programming (II)

http://poj.org/problem?id=2486

Given undirected tree with N nodes (1..N) Wi for node i (1<=i<=N) Gain Wi score when you FIRST visit node i Start from node 1 At most K step Output: Max score N<=100; K<=200;

Page 7: Dynamic Programming (II)

DFS from node 1 dp[i][j][0]:

max score obtained in subtree rooted at node i starting at node i walk at most j step back to node i

dp[i][j][1]: max score obtained in subtree rooted at node i starting at node i walk at most j step May NOT back to node i

Ans = dp[1][K][1]

Page 8: Dynamic Programming (II)

http://poj.org/problem?id=1947

Given unrooted tree with N nodes Output min number of edges whose

destruction would isolate a subtree with exactly P nodes

1 <= N <= 150; 1 <= P <= N;

Page 9: Dynamic Programming (II)

dp[i][j]: min number of edges destruction to isolate a subtree rooted at i and with j nodes

Consider child x If reserve x,

dp[i][j] = min(dp[i][j-k]+dp[x][k]) 0 <= k <= j Else

dp[i][j] = dp[i][j] + 1 Ans: min{dp[i][P]}

Page 10: Dynamic Programming (II)

http://codeforces.com/problemset/problem/132/D

You are given an integer n. You have to represent it as n = a1 + a2 + ... + am, where each of ai is a non-negative power of 2, possibly multiplied by -1.

Find a representation which minimizes the value of m.

Input: positive integer n, written as its binary notation. The length of the notation is at most 106.

Page 11: Dynamic Programming (II)

http://codeforces.com/problemset/problem/95/E Positive integers are lucky if their it doesn't contain

digits other than 4 and 7. Each island belongs to exactly one region, there is

a path between any two islands located in the same region; there is no path between any two islands from different regions.

A region is lucky if the amount of islands in it is a lucky number.

Find the minimum number of roads needed to build to create a lucky region.

n: number of islands; m: the number of roads 1 ≤ n, m ≤ 105

Page 12: Dynamic Programming (II)

http://codeforces.com/problemset/problem/176/D

A Hyper String is made by concatenation of some base strings. Suppose you are given a list of base strings b1, b2, ..., bn. Now the Hyper String made from indices list i1, i2, ..., im is concatenation of base strings bi1, bi2, ..., bim.

Compute the length of the longest common sub-sequence of a Hyper String t with a string s

1 ≤ n ≤ 2000 1 ≤ m ≤ 2000

Page 13: Dynamic Programming (II)

Tree DP NOI 2003 逃学的小孩 NOI 2002 贪吃的九头龙 Ural 1031 1039 1056 1073 1078 POJ 1947 1155 1655 3107 2486

http://codeforces.com/problemset/tags/dp