There is a state (territory) which is a tree rooted at node 1. All the cities (numbered from 1 to N+1)
in this state are connected via bidirectional roads. You have to add toll tax on each road. There are N roads which connect the cities of the state. You have to assign toll taxes on the roads so as to maximize the function Toll described below:
for(i=1;i<=number of cities;i++)
{
for(j=i+1;j<=number of cities;j++)
{
toll+=(toll required to pay to travel from i to j)
}
}
You have to maximize the toll tax. Assign the roads by toll taxes from the given array A(using each value exactly once). Find the maximum toll obtained.
Input Format:
First line contains
N and an integer whose value is always 2.
Then,
N roads follow containing 2 integers u and v, denoting the cities
between which the road is.
Next line contains N space separated values denoting elements of array A.
Output Format
Print the maximum toll which can be obtained.
Input Constraints
1≤N≤2∗10^5
1≤A[i]≤1000
1≤u,v≤N+1
Sample Input
2 2
1 3
2 3
5 7
Sample Output
24
Explanation
Assign 5 to edge (1- 3) and 7 to edge (2 - 3). This leads to an maximum toll tax of 24.
First, when you look at your Toll function code and Sample Input, then you'll see that this function counts just paths:
from 1 to 3
from 2 to 3
but not 3 to 1
and not 3 to 2,
because j is always more than i, so this leads us that 24 is incorrect answer (or you have incorrect Toll) function.
Second, according to the task (but I believe it just was described wrong) the answer will be always equal to sum of elements from array A, because the task sounds like : put elements to a symmetric matrix and then calculate a sum above (or below) a diagonal, but it is going to be all of the same elements from array A.
The Question you asked belongs to Graph.
Three cities are given from 1 -> 3. If you randomly assign values from A[] and use that in the toll function you will get the following output:
Assume you assigned 5 to Edge 1-3, and 7 to edge 2-3,
The graph would be like 1------3------2
Then According to the toll function, you will get the following routes:
1-2 === 7 + 5 = 12
1-3 === 5
2-3 === 7
So , the total toll would be = 12+5+7 = 24.
Hence, you need to first construct the graph . then assign the tolls randomly and find toll money for all the possible combinations.
or else,
you can use concept of Minimum Spanning Tree for Graph. You just need to inverse the use of kruskal or Prim's algorithm to find a route with maximum toll
PS: The meaning of bi-directional road is that suppose your first for loop starts from 3 and second for loop starts from 1, then you can also go 3->1 whose toll would be same as you used before for 1->3.
Hope this helps. :)
Related
I was solving problems on a competitive coding website when I came across this. The problem states that:
In this game there are N levels and M types of available weapons. The levels are numbered from 0 to N-1 and the weapons are numbered from 0 to M-1 . You can clear these levels in any order. In each level, some subset of these M weapons is required to clear this level. If in a particular level, you need to buy x new weapons, you will pay x^2 coins for it. Also note that you can carry all the weapons you have currently to the next level . Initially, you have no weapons. Can you find out the minimum coins required such that you can clear all the levels?
Input Format
The first line of input contains 2 space separated integers:
N = the number of levels in the game
M = the number of types of weapons
N lines follows. The ith of these lines contains a binary string of length M. If the jth character of
this string is 1 , it means we need a weapon of type j to clear the ith level.
Constraints
1 <= N <=20
1<= M <= 20
Output Format
Print a single integer which is the answer to the problem.
Sample TestCase 1
Input
1 4
0101
Output
4
Explanation
There is only one level in this game. We need 2 types of weapons - 1 and 3. Since, initially Ben
has no weapons he will have to buy these, which will cost him 2^2 = 4 coins.
Sample TestCase 2
Input
3 3
111
001
010
Output
3
Explanation
There are 3 levels in this game. The 0th level (111) requires all 3 types of weapons. The 1st level (001) requires only weapon of type 2. The 2nd level requires only weapon of type 1. If we clear the levels in the given order(0-1-2), total cost = 3^2 + 0^2 + 0^2 = 9 coins. If we clear the levels in the order 1-2-0, it will cost = 1^2 + 1^2 + 1^2 = 3 coins which is the optimal way.
Approach
I was able to figure out that we can calculate the minimum cost by traversing the Binary Strings in a way that we purchase minimum possible weapons at each level.
One possible way could be traversing the array of binary strings and calculating the cost for each level while the array is already arranged in the correct order. The correct order should be when the Strings are already sorted i.e. 001, 010, 111 as in case of the above test case. Traversing the arrays in this order and summing up the cost for each level gives the correct answer.
Also, the sort method in java works fine to sort these Binary Strings before running a loop on the array to sum up cost for each level.
Arrays.sort(weapons);
This approach work fine for some of the test cases, however more than half of the test cases are still failing and I can't understand whats wrong with my logic. I am using bitwise operators to calculate the number of weapons needed at each level and returning their square.
Unfortunately, I cannot see the test cases that are failing. Any help is greatly appreciated.
This can be solved by dynamic programming.
The state will be the bit mask of weapons we currently own.
The transitions will be to try clearing each of the n possible levels in turn from the current state, acquiring the additional weapons we need and paying for them.
In each of the n resulting states, we take the minimum cost of the current way to achieve it and all previously observed ways.
When we already have some weapons, some levels will actually require no additional weapons to be bought; such transitions will automatically be disregarded since in such case, we arrive at the same state having paid the same cost.
We start at the state of m zeroes, having paid 0.
The end state is the bitwise OR of all the given levels, and the minimum cost to get there is the answer.
In pseudocode:
let mask[1], mask[2], ..., mask[n] be the given bit masks of the n levels
p2m = 2 to the power of m
f[0] = 0
all f[1], f[2], ..., f[p2m-1] = infinity
for state = 0, 1, 2, ..., p2m-1:
current_cost = f[state]
current_ones = popcount(state) // popcount is the number of 1 bits
for level = 1, 2, ..., n:
new_state = state | mask[level] // the operation is bitwise OR
new_cost = current_cost + square (popcount(new_state) - current_ones)
f[new_state] = min (f[new_state], new_cost)
mask_total = mask[1] | mask[2] | ... | mask[n]
the answer is f[mask_total]
The complexity is O(2^m * n) time and O(2^m) memory, which should be fine for m <= 20 and n <= 20 in most online judges.
The dynamic optimization idea by #Gassa could be extended by using A* by estimating min and max of the remaining cost, where
minRemaining(s)=bitCount(maxState-s)
maxRemaining(s)=bitCount(maxState-s)^2
Start with a priority queue - and base it on cost+minRemaining - with the just the empty state, and then replace a state from this queue that has not reached maxState with at most n new states based the n levels:
Keep track bound=min(cost(s)+maxRemaining(s)) in queue,
and initialize all costs with bitCount(maxState)^2+1
extract state with lowest cost
if state!=maxState
remove state from queue
for j in 1..n
if (state|level[j]!=state)
cost(state|level[j])=min(cost(state|level[j]),
cost(state)+bitCount(state|level[j]-state)^2
if cost(state|level[j])+minRemaining(state|level[j])<=bound
add/replace state|level[j] in queue
else break
The idea is to skip dead-ends. So consider an example from a comment
11100 cost 9 min 2 max 4
11110 cost 16 min 1 max 1
11111 cost 25 min 0 max 0
00011 cost 4 min 3 max 9
bound 13
remove 00011 and replace with 11111 (skipping 00011 since no change)
11111 cost 13 min 0 max 0
11100 cost 9 min 2 max 4
11110 cost 16 min 1 max 1
remove 11100 and replace with 11110 11111 (skipping 11100 since no change):
11111 cost 13 min 0 max 0
11110 cost 10 min 1 max 1
bound 11
remove 11110 and replace with 11111 (skipping 11110 since no change)
11111 cost 11 min 0 max 0
bound 11
Number of operations should be similar to dynamic optimization in the worst case, but in many cases it will be better - and I don't know if the worst case can occur.
The logic behind this problem is that every time you have to find the minimum count of set bits corresponding to a binary string which will contain the weapons so far got in the level.
For ex :
we have data as
4 3
101-2 bits
010-1 bits
110-2 bits
101-2 bits
now as 010 has min bits we compute cost for it first then update the current pattern (by using bitwise OR) so current pattern is 010
next we find the next min set bits wrt to current pattern
i have used the logic by first using XOR for current pattern and the given number then using AND with the current number(A^B)&A
so the bits become like this after the operation
(101^010)&101->101-2 bit
(110^010)&110->100-1 bit
now we know the min bit is 110 we pick it and compute the cost ,update the pattern and so on..
This method returns the cost of a string with respect to current pattern
private static int computeCost(String currPattern, String costString) {
int a = currPattern.isEmpty()?0:Integer.parseInt(currPattern, 2);
int b = Integer.parseInt(costString, 2);
int cost = 0;
int c = (a ^ b) & b;
cost = (int) Math.pow(countSetBits(c), 2);
return cost;
}
[Interview Question] I got this question in a recent online interview. I had no clue how to solve it. Can anyone please help me solve this so that I can learn in Java.
Tom is very good in problem-solving. So to test Tom's skills, Jerry asks Tom a graph problem. Jerry gives Tom, an array A of N integers.
A graph is a simple graph, iff it has no self-loop or multi-edges.
Now Jerry asks Tom whether he can design a simple graph of N vertices or not. The condition is that Tom has to use each and every element of A exactly once for the degrees of vertices of the graph.
Now, Tom wants your help to design his graph. Print "YES" if the graph can be designed, otherwise print "NO" (without quotes).
Input
A single integer T, in the first line, denoting the number of test cases.
For each test case, there are 2 lines.
The first line is a single integer N, denoting the number of elements of array A.
The second line has N-space separated integers, representing elements of A.
Output
For each test case, print "YES" or "NO" (without quotes) whether the graph can be designed or not, in a new line.
Constraints
1<= T <= 100
1<= N <= 100
0<= Element of A <= 5000
Sample Test Cases
Input
1
2
1 1
Output
YES
Explanation
For this test case, a simple graph with 2 vertices can be designed, where each vertex has degree 1.
Input
2
3
1 2 1
3
1 1 1
Output
YES
NO
Explanation
For the first test case, we can design a simple graph of 3 vertices, which has degree sequence as [1, 2, 1]. The first vertex has degree 1, second, has 2 and third has 1.
For the second test case, we cannot make a simple graph of 3 vertices, which has degree sequence as [1, 1, 1].
One necessery condition is that sum of elements in A is even. That is due each edge
is counted twice in adjencency list.
Next is to try to construct graph, or at least 'allocate' pairs of nodes.
Sort elements of A in decending order,
Let the largest (first) element be a,
Check are element on positions 2 to a+1 larger than 0,
If there is a element with value 0 than it is not possible to construct a graph,
Decrease these a elements by 1 and set first element to 0,
Repeat process until all elements are 0.
Note that sorting in subsequent steps can be done in O(n) with merge sort step, since list consists
of three sorted parts:
first element (0) which can go to the end,
sorted part with a elements,
rest which is also sorted.
I was solving a problem which states following:
There are n buckets in a row. A gardener waters the buckets. Each day he waters the buckets between positions i and j (inclusive). He does this for t days for different i and j.
Output the volume of the waters in the buckets assuming initially zero volume and each watering increases the volume by 1.
Input: first line contains t and n seperated by spaces.
The next t lines contain i and j seperated by spaces.
Output: a single line showing the volume in the n buckets seperated by spaces.
Example:
Input:
2 2
1 1
1 2
Output:
2 1
Constraints:
0 <= t <= 104; 1 <= n <= 105
I tried this problem. But I use O(n*t) algorithm. I increment each time the bucket from i to j at each step. But this shows time limit error. Is there any efficient algorithm to solve this problem. A small hint would suffice.
P.S: I have used C++ and Java as tags bcoz the program can be programmed in both the languages.
Instead of remembering the amount of water in each bucket, remember the difference between each bucket and the previous one.
have two lists of the intervals, one sorted by upper, one by lower bound
then iterate over n starting with a volume v of 0.
On each iteration over n
check if the next interval starts at n
if so increase v by one and check the next interval.
do the same for the upper bounds but decrease the volume
print v
repeat with the next n
I think the key observation here is that you need to figure out a way to represent your (possibly) 105 buckets without actually allocating space for each and every one of them, and tracking them separately. You need to come up with a sparse representation to track your buckets, and the water inside.
The fact that your input comes in ranges gives you a good hint: you should probably make use of ranges in your sparse representation. You can do this by just tracking the buckets on the ends of each range.
I suggest you do this with a linked list. Each list node will contain 2 pieces of information:
a bucket number
the amount of water in that bucket
You assume that all buckets between the current bucket and the next bucket have the same volume of water.
Here's an example:
Input:
5 30
1 5
4 20
7 13
25 30
19 27
Here's what would happen on each step of the algorithm, with step 1 being the initial state, and each successive step being what you do after parsing a line.
1:0→NULL (all buckets are 0)
1:1→6:0→NULL (1-5 have 1, rest are 0)
1:1→4:2→6:1→21:0→NULL (1-3 have 1, 4-5 have 2, 6-20 have 1, rest have 0)
1:1→4:2→6:1→7:2→14:1→21:0→NULL
1:1→4:2→6:1→7:2→14:1→21:0→25:1→NULL
1:1→4:2→6:1→7:2→14:1→19:2→21:1→25:2→28:1→NULL
You should be able to infer from the above example that the complexity with this method is actually O(t2) instead of O(n×t), so this should be much faster. As I said in my comment above, the bottleneck this way should actually be the parsing and output rather than the actual computation.
Here's an algorithm with space and time complexity O(n)
I am using java since I am used to it
1) Create a hashset of n elements
2) Each time a watering is made increase the respective elements count
3) After file parsing is complete then iterate over hashset to calculate result.
Had a question regarding generating a list of 10-digit phone numbers on a PhonePad, given a set of possible moves and a starting number.
The PhonePad:
1 2 3
4 5 6
7 8 9
* 0 #
Possible moves:
The same number of moves a Queen in chess can make (so north, south, east, west, north-east, north-west, south-east, south-west... n-spaces per each orientation)
Starting number: 5
So far I have implemented the PhonePad as a 2-dimensional char array, implemented the possible moves a Queen can make in a HashMap (using offsets of x and y), and I can make the Queen move one square using one of the possible moves.
My next step is to figure out an algorithm that would give me all 10-digit permutations (phone numbers), using the possible moves in my HasMap. Repetition of a number is allowed. * and # are not allowed in the list of phone numbers returned.
I would imagine starting out with
- 5555555555, 5555555551, 5555555552... and so on up to 0,
- 5555555515, 5555555155, 5555551555.. 5155555555.. and with the numbers 2 upto 0
- 5555555151, 5555551515, 5555515155.. 5151555555.. and with numbers 2 upto 0
... and so on for a two digit combination
Any suggestions on a systematic approach generating 10-digit combinations? Even a pseudocode algorithm is appreciated! Let me know if further clarification is required.
Thanks in advance! :)
In more detail, the simplest approach would be a recursive method, roughly like:
It accepts a prefix string initially empty, a current digit (initially '5'), and a number of digits to generate (initially 10).
If the number of digits is 1, it will simply output the prefix concatenated with the current digit.
If the number of digits is greater than 1, then it will make a list of all possible next digits and call itself recursively with (prefix + (current digit), next digit, (number of digits)-1 ) as the arguments.
Other approaches, and refinements to this one, are possible of course. The "output" action could be writing to a file, adding to a field in the current class or object, or adding to a local variable collection (List or Set) that will be returned as a result. In that last case, the (ndigits>1) logic would have to combine results from multiple recursive calls to get a single return value.
This question already has answers here:
Closed 11 years ago.
Possible Duplicate:
Can you answer this 2009 ACM International Collegiate Programming Contest Finals problem?
Hi,
I am attempting to do question 1 here-> http://cm.baylor.edu/ICPCWiki/attach/Problem%20Resources/2009WorldFinalProblemSet.pdf
and cannot really come up with a good algorithm to solve it :
Basically, there are n planes, n is read in from standard input. There are then n intervals for times in which the planes can arrive, you must compute the largest interval between all planes that is possible. So, say
n = 3
and you are given the inputs
0 10
5 15
10 15
The answer is : 7: 30, the largest possible interval between planes.
Not really sure how I would go about solving this. Any tips ?
For the first plane, select the earliest possible arrival time
For the last plane, select the latest possible arrival time
For elements 2 through element n-1:
Search for a midpoint plane by dividing the range between element 1 and element n
(Hopefully, that will be close to the element n/2)
recursivly call the same function for element 1 and the midpoint element
recursivly call the same function for the element after the midpoint element and element n
That will evenly divide up the time available within the constraints of the planes scheduled windows.
Once you have roughly evenly spaced windows, select the smallest window and test it with its neighboring planes to see if they can shift some to expand the smallest window. Repeat this process until the smallest window can't shift a significent amount.