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# PRINDRAG - Editorial

Practice

Contest

Author: Stepan Filippov

Tester: Mark Mikhno

Editorialist: Bhuvnesh Jain

MEDIUM-HARD

# Prerequisites

Dynamic Programming

# Problem

You are given a list of $N$ dragons each having some power $A[i]$. There is a prince with power $W$. The princess decides to sit at position $x, 1 <= x <= N$. The prince starts from any position towards the princess and loses power equal to $A[i]$ when he is at index $i$. If dies at any moment are power becomes non-positive. She wants to arrange the dragons in such a way such that the number of positions from which prince dies before reaching her is maximised. She want to calculate this value for all $x, 1 <= x <= N$.

# Explanation

The first to note is that we would always like to place stronger dragons close to the princess as it will increase the number of positions from which prince would die. This equivalently means, we would like to have the minimum number of dragons such that their sum of powers exceeds $W$. For this, we have two conditions, either we place dragons on both sides such that their sum of powers exceeds $W$, meaning there are places on both sides such that the princess will die. In another case, we place dragons on one side only such that their sum of powers exceeds $W$ so that princess doesn't die from one side but dies from some places on another side.

The other thing to note is that the largest dragon will always stay at the place the princess is staying. This is consistent with the fact that the princess wants stronger dragons to stay close to her so that prince dies from the maximum number of starting positions. So, when considering dragons to be placed on both sides to defeat the prince, this dragon will be counted twice and this needs to be taken care in implementation.

Now, in both cases we have the following reduced problems:

1. For one side case, we need to find the minimum number of dragons such that the sum of their powers is greater than or equal to $W$.

2. For both side case, we need to find minimum number of dragons such that for index $i$, there is partition of size less than or equal to $(i - 1)$ with sum of powers greater than or equal to $W$ and other disjoint partition of size less than or equal to $(N - i)$ such that sum of powers is greater than or equal to $W$.

The answer for each index is basically the maximum answer we can obtain from both cases.

For the first case, the answer can be found greedily by simply placing the dragons in decreasing order of power and finding the first index such that sum of powers till now is greater than or equal to $W$. Let us denote this value by $z$.

For the second case, let us simply the problem further. For this, let us think if the size of partitions really matter, (i.e. do we care about the index $i$ for which the calculation is being done). So, let us assume the optimal partitions of dragons into $2$ disjoint sets such that the sum of both is greater than or equal to $W$ have sizes $x$ and $y$. It is evident that $z <= x$ and $z <= y$. For now, assume left size size is less than right side size i.e. $(i - 1) < (N - i)$. Also, $x <= y$.

If $x <= (i - 1)$ and $(y <= (N - i))$, then everything is good. Assume $x > (i - 1)$, o dragons can't protect the princess from the left side and $y$ dragons protect the princess from the right side. In this case, it is better to choose $z$ dragons only to protect the princess from one side as $z <= y$ and it makes our answer better. So, the size of $x$ and $y$ don't matter in this case. Again if $x > (i - 1)$ and $y > (N - i)$, it means princess can never be protected from both sides and we need to consider the answer for one side case only, meaning sizes of $x$ and $y$ don't matter again.

We can prove it for other cases like $(i - 1) > (N - i)$ similarly. Thus, we conclude size of partition don't matter and the reduced problem is therefore

Find the minimum sum of $x$ and $y$ such that there is a disjoint partition of size $x$ and $y$ such that sum of powers of the dragon in both partitions is greater than $W$

Let us first calculate the minimum number of dragons required to obtain the sum of powers as greater than or equal to $U$. This is the same as the reduced problem $1$. We will calculate this value for every $U$, $1 <= U <= 3 * W$, as till will be required later.

For this, we will use dynmaic programming solution. Let $dp[i] = 1$ if there exists a partiton of dragons such that their sum of powers is exactly $i$. Otherwise, $dp[i] = 0$.

We will process all equal powers simultaneously. Let the current power be $u$. We consider the sum of partitions $A$ and $B$. Let $A = j + k * u$, for valid $j$ and $k$. We need $A >= W$, meaning for given $j$, we can find the minimum number of dragons required for $A >= W$. The only other condition is $B >= W$. So, we need to find the minimum number of dragons with the sum of powers as $(A + W)$. This can be done using the previous pre-computation we did. We can thus update our answer, only if $dp[j]$ is set. This is because, if $dp[j]$ is not set, we can't obtain partition for $A$.

Now, we need to update the possible $dp[j]$ values as we can use some number $u$. For this, we consider another dynamic programming, $gp[v]$ denoting minimum number of $u$ required to set $dp[v]$. The trivial case is when $dp[v]$ is already set, meaning $gp[v] = 0$. For other cases, we try to extend the solution for $(v - u)$ by $1$, meaning extend the sequence by $u$.

Once, $gp[v]$ is calcualted, we update the $dp[v]$ as follows: $dp[v] = dp[v] or (gp[v] <= m)$ where $m$ is the number of dragons with power $u$. This works because:

1. If $dp[v]$ was already set, we ignore it.
2. If $gp[v] > m$, we don't have required number of dragons with power $u$.
3. If $v < u$, then we should have $gp[v] = inf$, i.e. a large value.
4. If $v == u$, then we have $gp[v] = 1$ and we can obtain $v$ using a dragon of power $u$.
5. If $v > u$, we can obtain $v$ only if we have suitable number of dragons with power $u$ i.e. $gp[v] <= m$. The proof lies in the way $gp[v]$ is constructed and extended using dragons of power $u$.

For details, I request you to go through the commented solution of the author below. The case analysis is explained in line with the editorial.

For time complexity analysis:

1. $O(W)$ for calculating $min_pref$ array in solution.
2. $O(min(N, W) * sqrt(W))$ for doing the dynamic programming solution for both sides.
3. $O(N)$ for calculating the final answer.

For case $2$, the proof (from author) is as follows:

We process all equal values $u$ in $O(W)$. Note that any $1.5 * sqrt(W)$ different positive numbers have $sum >= W$, so if we take $3 * sqrt(W)$ different positive numbers we can split the into two sets with $sums >= W$. My solution breaks the loop when $p >= ans$. If we've processed $3 * sqrt(W)$ different numbers then we've found the partition into two sets containing at most $3 * sqrt(W)$ different values. Let $q$ be the index of $(3 * sqrt(W)+1)th$ value. When $(p = q)$ variable $(ans < q)$, but all next possible partitions will contain $q$, so they won't be optimal. So we can safely break our loop.

So the time complexity is O(min(N, sqrt(W)) * W).

If your solution was somewhat different, feel free to share in the comments section below.

# Time Complexity

$O(N + W + min(N, W) * sqrt(W))$

# Space Complexity

$O(N + W)$

# SOLUTIONS:

Author's solution can be found here.

Tester's solution can be found here.

This question is marked "community wiki".

6★likecs
3.7k1978
accept rate: 9%

 4 This was a nice problem. At first it looked difficult, but then I noticed that for all $i$ you ever only need at most two different optimal arrangements of the dragons, one single sided and one double sided. By optimal I mean the arrangement using the fewest number of dragons to kill the prince. This is because if an optimal double sided arrangement doesn't fit for some $i$, then an optimal single sided arrangement is better. This is because cutting off a double sided arrangement will simply make it better. This also means that the solution to the problem will always have a \_/ shaped answer, something like 5 4 3 2 2 3 4 5. For small $i$ and large $i$ a single sided arrangement is optimal, creating the slopes \ and /. And in the middle the double sided arrangement could be better, creating the flat _. answered 22 Aug, 02:53 714●2●10 accept rate: 37%
 0 what i tried to do is sort dragons according to powers. Now I fixed most powerful dragon at center and tried to calculate how many dragons i need to beat the prince at minimum. at each step I checked if there's a dragon with power just greater than prince if there is one I have my answer if not reduce prince's power by maximum dragon. I repeat the above steps calculate the Number of dragons for one side. Do this similarly for other side. now for each i ,check if one can protect princess both ways or only one way. But i failed 4-5 cases I dont understand why? solution link https://www.codechef.com/viewsolution/19716204 answered 26 Aug, 22:19 1 accept rate: 0%
 0 Can someone plz explain everything after this: Find the minimum sum of x and y such that there is a disjoint partition of size x and y such that sum of powers of the dragon in both partitions is greater than W. answered 28 Sep, 02:19 1●2 accept rate: 0%
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