I just want a direction in this programming problem from an online judge (URI online judge - 2699).
Given two numbers, S and N, S is incomplete, so S can be given in the form ?294?? where the first digit is not zero, I need to find the minimum number that has the same digits as S and is multiple of N. If is not possible, then you just return a *. S can have up to 1000 digits and N < 1000.
I will describe my attempts:
Brute Force: I try every combination of numbers and get the first one to be multiple of N. Finding a solution when it exists is not the problem at all, but discovering that does not exist a solution when S is big can be really problematic and take infinite time.
Brute Force but optimizing the form of finding the rest: This attempt i save into an array the rest of the division for the digit 1 in the i position, so for i = 3, in v[3] i will have 1000%N. Knowing that (AB) MOD N = ((A MOD N)B) MOD N it's possible to write an array pretty quick and optimize the way i calculate the Mod of S which. This attempt does improve the time but is a Brute Force Attempt and has the same issues that the previous one.
Using the remainder to do the recursion: Ex: If i have the number
?294?? in S, i get the remainder of 29400 and calculate how much is needed to have a multiple (N - rem), then i try to get it all from the first digit, if it is not possible then i decrease how much I want and try again, then I go to the left and try with another number. Ex if i need 7 to reach N and can get 5 with the first digit, then I will try to find 2 within the second digit and so on.
Does it have a concept that i ain't seeing here ? I'm trying this problem for almost 3 days, searching ways to do this and not getting anywhere because of time.
EDIT: Thanks for the comments, after thinking all day about this problem and reading a lot of Dynamic Programming I could figure a way to apply DP in this problem, I won't say exactly how but the key is to understand DP and figure a way to reduce the size of your problem.
I am completely and utterly brand new to this and trying to teach myself Ruby. I have been given a question to see if I can piece together what to do and prove problem solving skills via research and sheer determination so, keep in mind, I know very little about Ruby, I have been learning it for all of a day.
I need to first determine if an integer is a prime number (without using the required 'prime' directory, as far as I know) and then, if the result is true, my output needs to be 1. If it is false, my output needs to be the smallest divisor greater than one.
Piecing together things I found here and various other sites around the internet, I put together something I hoped would work. It does not.
def isPrime(n)
( 2..Math.sqrt(n)).each { |i|
if n % i == 0 && i < n
else
n.reduce { |smallest, current| break if n <= 2 }
puts n
end
}
1
I haven't the foggiest idea why it doesn't work. I know little about Ruby's syntax and I am reasonably certain that is where I am messing up.
Finding the prime number DOES work; it's the rest (finding the smallest divisor) that does not. And I'm sure my replacing true with 1 is mangling this horribly. Any help or insight would be greatly appreciated. I have zero background in coding (unless you count my mom working in COBOL in the 80s) so, by all means, explain it like you would to a simpleton because I am THAT new.
Today while going through a random video on youtube, I learn't about a very interesting law called Benford's law. I was wondering if it is possible to write a code to verify it for a^n.
I want to write a code that prints the first digit of 2^n where n is of order 10^5. Is it possible to write a code for it?
I know I haven't posted any code sample or shown any research effort.I am unable to think of any algorithm for it.
Use logarithms.
log_10(2) = 0.30102999566
log_10(2^100000) = 30102.999566
In other words, 2^100000 is a 30103-digit number, whose first digit can be found from the fractional part of this number:
10^0.999566 = 9.9900..
I was asked the following question in an interview. I don't have any idea about how to solve this. Any suggestions?
Given the start and an ending integer as user input,
generate all integers with the following property.
Example:
123 , 1+2 = 3 , valid number
121224 12+12 = 24 , valid number
1235 1+2 = 3 , 2+3 = 5 , valid number
125 1+2 <5 , invalid number
A couple of ways to accomplish this are:
Test every number in the input range to see if it qualifies.
Generate only those numbers that qualify. Use a nested loop for the two starting values, append the sum of the loop indexes to the loop indexes to come up with the qualifying number. Exit the inner loop when the appended number is past the upper limit.
The second method might be more computationally efficient, but the first method is simpler to write and maintain and is O(n).
I don't know what the interviewer is looking for, but I would suspect the ability to communicate is more important than the answer.
The naive way to solve this problem is by iterating the numbers in the set range, parsing the numbers into a digit sequence and then testing the sequence according to the rule. There is an optimization in that the problem essentially asks you to find fibonnaci numbers so you can use two variables or registers and add them sequentially.
It is unclear from your question whether the component numbers have to have the same number of digits. If not, then you will have to generate all the combinations of the component number arrangements.
First off, let me say that this is not homework (I am an A-Level student, this is nothing close to what we problem solve (this is way harder)), but more of a problem I'm trying to suss out to improve my programming logic.
I thought of a scenario where there is an array of random integers, let's for example say 10 integers. The user will input a number he wants to count to, and the algorithm will try and work out what numbers are needed to make that sum. For example if I wanted to make the sum 44 from this array of integers:
myIntegers = array(1, 5, 9, 3, 7, 12, 36, 22, 19, 63);
The output would be:
36 + 3 + 5 = 44
Or something along those lines. I hope I make myself clear. As an added bonus I would like to make the algorithm pick as few numbers as possible to make the required sum, or give out an error if the sum cannot be made with the numbers supplied.
I thought about using recursion and iterating through the array, adding numbers over and over until the sum is met or gone past. But what I can't get my head around is what to do if the algorithm goes past the sum and needs to be selective about what numbers to pick from the array.
I'm not looking for complete code, or a complete algorithm, I just want your opinions on how I should proceed with this and perhaps share a few tips or something. I'll probably start work on this tonight. :P
As I said, not homework. Just me wanting to do something a bit more advanced.
Thanks for any help you're able to offer. :)
You are looking at the Knapsack Problem
The knapsack problem or rucksack problem is a problem in combinatorial optimization: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than a given limit and the total value is as large as possible. It derives its name from the problem faced by someone who is constrained by a fixed-size knapsack and must fill it with the most useful items.
Edit: Your special case is the Subset Sum Problem
Will subset sum do? ;]
This is the classic Knapsack problem that you would see in college level algorithms course (or at least I saw it then). Best to work this out on paper and the solution in code should be relatively easy to work out.
EDIT: One thing to consider is dynamic programming.
Your Problem is related to the subset sum problem.
You have to try all possible combinations in the worst case.
No shortcuts here I'm afraid. In addition to what other people have said, about what specific problem this is etc., here's some practical advice to offer you a starting point:
I would sort the array and given the input sum m, would find the first number in the array less than m, call it n (this is your first possible number for the sum), and start from the highest possible complement (m-n), working your way down.
If you don't find a precise match, pick the highest available, call it o, (that now is your 2nd number) and look for the 3rd one starting from (m-n-o) and work your way down again.
If you don't find a precise match, start with the next number n (index of original n at index-1) and do the same. You can keep doing this until you find a precise match for two numbers. If no match for the sum is found for two numbers, start the process again, but expand it to include a 3rd number. And so on.
That could be done recursively. At least this approach ensures that when you find a match, it will be the one with the least possible numbers in the set forming the total input sum.
Potentially though, worst case, you end up going through the whole lot.
Edit: As Venr correctly points out, my first approach was incorrect. Edited approach to reflect this.
There is a very efficient randomized algorithm for this problem. I know you already accepted an answer, but I'm happy to share anyway, I just hope people will still check this question :).
Let Used = list of numbers that you sum.
Let Unused = list of numbers that you DON'T sum.
Let tmpsum = 0.
Let S = desired sum you want to reach.
for ( each number x you read )
toss a coin:
if it's heads and tmpsum < S
add x to Used
else
add x to Unused
while ( tmpsum != S )
if tmpsum < S
MOVE one random number from Unused to Used
else
MOVE one random number from Used to Unused
print the Used list, containing the numbers you need to add to get S
This will be much faster than the dynamic programming solution, especially for random inputs. The only problems are that you cannot reliably detect when there is no solution (you could let the algorithm run for a few seconds and if it doesn't finish, assume there is no solution) and that you cannot be sure you will get the solution with minimum number of elements chosen. Again, you could add some logic to make the algorithm keep going and trying to find a solution with less elements until certain stop conditions are met, but this will make it slower. However, if you are only interested in a solution that works and you have a LOT of numbers and the desired sum can be VERY big, this is probably better than the DP algorithm.
Another advantage of this approach is that it will also work for negative and rational numbers with no modifications, which is not true for the DP solution, because the DP solution involves using partial sums as array indexes, and indexes can only be natural numbers. You can of course use hashtables for example, but that will make the DP solution even slower.
I don't know exactly what's this task is called, but it seems that it's kind of http://en.wikipedia.org/wiki/Knapsack_problem.
Heh, I'll play the "incomplete specification" card (nobody said that numbers couldn't appear more than once!) and reduce this to the "making change" problem. Sort your numbers in decreasing order, find the first one less than your desired sum, then subtract that from your sum (division and remainders could speed this up). Repeat until sum = 0 or no number less than the sum is found.
For completeness, you would need to keep track of the number of addends in each sum, and of course generate the additional sequences by keeping track of the first number you use, skipping that, and repeating the process with the additional numbers. This would solve the (7 + 2 + 1) over (6 + 4) problem.
Repeating the answer of others: it is a Subset Sum problem.
It could be efficiently solved by Dynamic Programing technique.
The following has not been mentioned yet: the problem is Pseudo-P (or NP-Complete in weak sense).
Existence of an algorithm (based on dynamic programming) polynomial in S (where S is the sum) and n (the number of elements) proves this claim.
Regards.
Ok, I wrote a C++ program to solve the above problem. The algorithm is simple :-)
First of all arrange whatever array you have in descending order(I have hard-coded the array in descending form but you may apply any of the sorting algorithms ).
Next I took three stacks n, pos and sum. The first one stores the number for which a possible sum combination is to be found, the second holds the index of the array from where to start the search, the third stores the elements whose addition will give you the number you enter.
The function looks for the largest number in the array which is smaller than or equal to the number entered. If it is equal, it simply pushes the number onto the sum stack. If not, then it pushes the encountered array element to the sum stack(temporarily), and finds the difference between the number to search for and number encountered, and then it performs recursion.
Let me show an example:-
to find 44 in {63,36,22,19,12,9,7,5,3,1}
first 36 will be pushed in sum(largest number less than 44)
44-36=8 will be pushed in n(next number to search for)
7 will be pushed in sum
8-7=1 will be pushed in n
1 will be pushed in sum
thus 44=36+7+1 :-)
#include <iostream>
#include<conio.h>
using namespace std;
int found=0;
void func(int n[],int pos[],int sum[],int arr[],int &topN,int &topP,int &topS)
{
int i=pos[topP],temp;
while(i<=9)
{
if(arr[i]<=n[topN])
{
pos[topP]=i;
topS++;
sum[topS]=arr[i];
temp=n[topN]-arr[i];
if(temp==0)
{
found=1;
break;
}
topN++;
n[topN]=temp;
temp=pos[topP]+1;
topP++;
pos[topP]=temp;
break;
}
i++;
}
if(i==10)
{
topP=topP-1;
topN=topN-1;
pos[topP]+=1;
topS=topS-1;
if(topP!=-1)
func(n,pos,sum,arr,topN,topP,topS);
}
else if(found!=1)
func(n,pos,sum,arr,topN,topP,topS);
}
main()
{
int x,n[100],pos[100],sum[100],arr[10]={63,36,22,19,12,9,7,5,3,1},topN=-1,topP=-1,topS=-1;
cout<<"Enter a number: ";
cin>>x;
topN=topN+1;
n[topN]=x;
topP=topP+1;
pos[topP]=0;
func(n,pos,sum,arr,topN,topP,topS);
if(found==0)
cout<<"Not found any combination";
else{
cout<<"\n"<<sum[0];
for(int i=1;i<=topS;i++)
cout<<" + "<<sum[i];
}
getch();
}
You can copy the code and paste it in your IDE, works fine :-)