Minimum number with 0 and 1 divisible by n [duplicate] - algorithm

Question

Every positive integer divide some number whose representation (base 10) contains only zeroes and ones.
One can prove that:
Consider the numbers 1, 11, 111, 1111, etc. up to 111... 1, where the
last number has n+1 digits. Call these numbers m1, m2, ... , mn+1. Each has a
remainder when divided by n, and two of these remainders must be the same.
Because there are n+1 of them but only n values a remainder can take.
This is an application of the famous and useful “pigeonhole principle”;
Suppose the two numbers with the same remainder are mi and mj
, with i < j. Now subtract the smaller from the larger. The resulting number, mi−mj, consisting of j - i ones followed by i zeroes, must be a multiple of n.
But how to find the smallest answer? and effciently?

Answer 1

The question equals to using 10i mod n (for each i, it can be used at most once) to get a sum m of n. It's like a knapsack problem or subset sum problem. In this way, dynamic programming will do the task.
In dynamic programming the complexity is O(k*n). k is the number of digits in answer. For n<105, this code works perfectly.
Code:
#include <stdio.h>
#define NUM 2000
int main(int argc, char* argv[])
{
signed long pow[NUM],val[NUM],x,num,ten;
int i,j,count;
for(num=2; num<NUM; num++)
{
for(i=0; i<NUM; pow[i++]=0);
count=0;
for(ten=1,x=1; x<NUM; x++)
{
val[x]=ten;
for(j=0; j<NUM; j++)if(pow[j]&&!pow[(j+ten)%num]&&pow[j]!=x)pow[(j+ten)%num]=x;
if(!pow[ten])pow[ten]=x;
ten=(10*ten)%num;
if(pow[0])break;
}
x=num;
printf("%ld\tdivides\t",x=num);
if(pow[0])
{
while(x)
{
while(--count>pow[x%num]-1)printf("0");
count=pow[x%num]-1;
printf("1");
x=(num+x-val[pow[x%num]])%num;
}
while(count-->0)printf("0");
}
printf("\n");
}
}
PS:
This sequence in OEIS.

Answer 2

Nice question. I use BFS to solve this question with meet-in-the-middle and some other prunings. Now my code can solve n<109 in a reasonable time.
#include <cstdio>
#include <cstring>
class BIT {
private: int x[40000000];
public:
void clear() {memset(x, 0, sizeof(x));}
void setz(int p, int z) {x[p>>5]=z?(x[p>>5]|(1<<(p&31))):(x[p>>5]&~(1<<(p&31)));}
int bit(int p) {return x[p>>5]>>(p&31)&1;}
} bp, bq;
class UNIT {
private: int x[3];
public: int len, sum;
void setz(int z) {x[len>>5]=z?(x[len>>5]|(1<<(len&31))):(x[len>>5]&~(1<<(len&31)));}
int bit(int p) {return x[p>>5]>>(p&31)&1;}
} u;
class MYQUEUE {
private: UNIT x[5000000]; int h, t;
public:
void clear() {h = t = 0;}
bool empty() {return h == t;}
UNIT front() {return x[h];}
void pop() {h = (h + 1) % 5000000;}
void push(UNIT tp) {x[t] = tp; t = (t + 1) % 5000000;}
} p, q;
int n, md[100];
void bfs()
{
for (int i = 0, tp = 1; i < 200; i++) tp = 10LL * (md[i] = tp) % n;
u.len = -1; u.sum = 0; q.clear(); q.push(u); bq.clear();
while (1)
{
u = q.front(); if (u.len >= 40) break; q.pop();
u.len++; u.setz(0); q.push(u);
u.setz(1); u.sum = (u.sum + md[u.len]) % n;
if (!bq.bit(u.sum)) {bq.setz(u.sum, 1); q.push(u);}
if (!u.sum) {
for (int k = u.len; k >= 0; k--) printf("%d", u.bit(k));
puts(""); return;
}
}
u.len = 40; u.sum = 0; p.clear(); p.push(u); bp.clear();
while (1)
{
u = p.front(); p.pop();
u.len++; u.setz(0); p.push(u);
u.setz(1); u.sum = (u.sum + md[u.len]) % n;
if (!bp.bit(u.sum)) {bp.setz(u.sum, 1); p.push(u);}
int bf = (n - u.sum) % n;
if (bq.bit(bf)) {
for (int k = u.len; k > 40; k--) printf("%d", u.bit(k));
while (!q.empty())
{
u = q.front(); if (u.sum == bf) break; q.pop();
}
for (int k = 40; k >= 0; k--) printf("%d", u.bit(k));
puts(""); return;
}
}
}
int main(void)
{
// 0 < n < 10^9
while (~scanf("%d", &n)) bfs();
return 0;
}

Answer 3

There's an O(n)-time (arithmetic operations mod n, really) solution, which is more efficient than the answer currently accepted. The idea is to construct a graph on vertices 0..n-1 where vertex i has connections to (i*10)%n and (i*10+1)%n, then use breadth-first search to find the lexicographically least path from 1 to 0.
def smallest(n):
parents = {}
queue = [(1 % n, 1, None)]
i = 0
while i < len(queue):
residue, digit, parent = queue[i]
i += 1
if residue in parents:
continue
if residue == 0:
answer = []
while True:
answer.append(str(digit))
if parent is None:
answer.reverse()
return ''.join(answer)
digit, parent = parents[parent]
parents[residue] = (digit, parent)
for digit in (0, 1):
queue.append(((residue * 10 + digit) % n, digit, residue))
return None

Answer 4

Here is a readable solution using BFS in java. The approach is similar to David's with some improvements.
You build a decision tree of whether to append a 0 or 1 and perform BFS to find the lowest such valid multiple of the input number.
This solution also leverages modulo (of the input number) to compute really large results. Full description available in the comments in the code.
You can also access the same code snippet in ideone.
import java.util.ArrayDeque;
import java.util.Arrays;
import java.util.HashSet;
import java.util.Queue;
import java.util.Scanner;
import java.util.Set;
public class Main {
// Return the smallest multiple of the number (as a string) consisting only of digits 0 and 1
//
// All possible digits that can be constructed using the digits 0/1 can be represented
// as a tree, where at each level, appending a 0 is one branch and appending a 1 is another
//
// If we perform BFS on this tree, the first number we see which is an exact multiple of the input
// number will be the result (since it will be the smallest). Make sure to consider left
// branch (i.e. 0) before considering the right branch (i.e. 1)
//
// The 2 paths we take at each level when the current number is num:
// (num * 10)
// (num * 10) + 1
//
// Since the result can grow huge quite easily, it might not be possible to store the result in a
// 32 or even a 64 bit int/long variable.
//
// One alternative is to use BigNumber, but a simpler alternative exists if we leverage modulo.
//
// The operations we perform above (i.e. multiplications and additions) will retain the useful part
// of the result when using modulo. We use the given number itself as the modulo, and when we see a
// result of 0, it means we have found a number which is an exact multiple of the input number.
//
// To reconstruct the number, we need to store the parent nodes of each node, when adding the node
// in the queue (similar to using BFS for computing shortest path)
//
// We will also need to know if we appended a 0 or a 1 at each step, and so we add this information
// as part of the node data structure as well.
//
// Re-visiting nodes is unecessary since we have seen this modulo result (i.e. value % num) already.
// Any additional digits we add from now will only make the number longer and we already are tracking
// the path for this same modulo result we've seen earlier.
//
public static String multiple(int num) {
if (num < 0) {
throw new IllegalArgumentException("Invalid args");
}
String result = "0";
if (num > 0) {
// An array to mark all the visited nodes
boolean[] isVisited = new boolean[num];
Arrays.fill(isVisited, false);
// The queue used by BFS
Queue<Node> queue = new ArrayDeque<>();
// Add the first number 1 and mark it visited
queue.add(new Node(true, 1 % num, null));
isVisited[1 % num] = true;
// The final destination node which represents the answer
Node destNode = null;
while (!queue.isEmpty()) {
// Get the next node from the queue
Node currNode = queue.remove();
if (currNode.val == 0) {
// We have reached a valid multiple of num
destNode = currNode;
break;
} else {
// Visit the next 2 neighbors
// Append 0 - (currNode.val * 10)
// Append 1 - (currNode.val * 10) + 1
// Append a '0'
int val1 = (currNode.val * 10) % num;
if (!isVisited[val1]) {
queue.add(new Node(false, val1, currNode));
isVisited[val1] = true;
}
// Append a '1'
int val2 = (val1 + 1) % num;
if (!isVisited[val2]) {
queue.add(new Node(true, val2, currNode));
isVisited[val2] = true;
}
}
}
// Trace the path from destination to source
if (destNode == null) {
throw new IllegalStateException("Result should not be null");
} else {
StringBuilder reverseResultBuilder = new StringBuilder();
Node currNode = destNode;
while (currNode != null) {
reverseResultBuilder.append(currNode.isDigitOne ? '1' : '0');
currNode = currNode.parent;
}
result = reverseResultBuilder.reverse().toString();
}
}
return result;
}
// Node represents every digit being appended in the decision tree
private static class Node {
// True if '1', false otherwise (i.e. '0')
public final boolean isDigitOne;
// The number represented in the tree modulo the input number
public final int val;
// The parent node in the tree
public final Node parent;
public Node(boolean isDigitOne, int val, Node parent) {
this.isDigitOne = isDigitOne;
this.val = val;
this.parent = parent;
}
}
public static void main(String[] args) {
int num = new Scanner(System.in).nextInt();
System.out.println("Input number: " + num);
System.out.println("Smallest multiple using only 0s and 1s as digits: " + Main.multiple(num));
}
}

Answer 5

I think this is a fair and interesting question.
Please note that though what you describe is a proof there always exist such number, the found number will not always be minimal.
Only solution I can think of is to compute the remainders of the powers of 10 modulus the given n and than try to construct a sum giving remainder 0 modulo n using at most one of each of these powers. You will never need more than n different powers(which you prove i your question).

Answer 6

This is a fast way to get the first 792 answers. Def the most simple code:
__author__ = 'robert'
from itertools import product
def get_nums(max_length):
assert max_length < 21 #Otherwise there will be over 2 million possibilities
for length in range(1, max_length + 1):
for prod in product("10", repeat=length):
if prod[0] == '1':
yield int("".join(prod))
print list(get_nums(4))
[1, 11, 10, 111, 110, 101, 100, 1111, 1110, 1101, 1100, 1011, 1010, 1001, 1000]
nums = sorted(get_nums(20))
print len(nums)
solution = {}
operations = 0
for factor in range(1, 1000):
for num in nums:
operations += 1
if num % factor == 0:
solution[factor] = num
break
print factor, operations
if factor not in solution:
print "no solution for factor %s" % factor
break
print solution[787]
max_v = max(solution.values())
for factor, val in solution.items():
if val == max_v:
print factor, max_v
[1, 11, 10, 111, 110, 101, 100, 1111, 1110, 1101, 1100, 1011, 1010, 1001, 1000]
1048575
1 1
2 3
3 10
4 14
5 16
6 30
7 39
8 47
9 558
10 560
11 563
12 591
13 600
14 618
15 632
16 648
17 677
18 1699
19 1724
20 1728
..
..
187 319781
188 319857
..
..
791 4899691
792 5948266
no solution for factor 792
10110001111
396 11111111111111111100

Answer 7

Here is a C# solution using linked list
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Collections;
namespace ConsoleApplication1
{
class Program
{
public static void print(LinkedList<int> lst)
{
foreach(int i in lst)
{
Console.Write(i);
}
}
static void Main(string[] args)
{
int number = Convert.ToInt32(Console.ReadLine());
int product;
LinkedList<int> list = new LinkedList<int>();
bool Istrue = true;
int range = 1;
while (range <= 10) {
Istrue = true;
product = number * range;
while (product > 0)
{
list.AddFirst(product % 10);
product /= 10;
}
foreach (int i in list)
{
if (i > 1) Istrue = false;
}
if (Istrue) { print(list); break; }
else
{
list.Clear();
}
range++;
}
Console.WriteLine("Done");
string s = Console.ReadLine();
}
}
}

Answer 8

My algorithm will be :-
1)Construct the sorted tree of of n possible numbers(say n initially is 10). So in this example it will contain 1,10,11,100,101,110,111....
2)Then loop over the list and perform on each no x%GivenNo, if its o its smallest possible no
3)Otherwise repeat step 3 with another 10 numbers

Answer 9

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
namespace ConsoleApplication2
{
class Class1
{
public static void Main()
{
List<string> possibleCombination = new List<string>();
for (int i = 2; i < 10000; i++)
{
possibleCombination.Add(Convert.ToString(i, 2));
}
var input = Console.ReadLine();
long output = 0;
foreach (var item in possibleCombination)
{
if (Convert.ToInt64(item) % Convert.ToInt64(i) == 0)
{
output = Convert.ToInt64(item);
break;
}
}
Console.WriteLine(output);
Console.ReadLine();
}
}
}

Answer 10

Here is complete c# code in O(n) using graph and bfs approach.
using System;
using System.Collections.Generic;
using System.Collections;
using System.Security.Cryptography;
using System.Linq;
using System.Runtime.InteropServices;
class Solution {
public class Edge : IComparable
{
public int From
{
get;
set;
}
public int To
{
get;
set;
}
public int Weight
{
get;
set;
}
public bool IsDirected
{
get;
set;
}
public Edge(int from, int to, bool isDirected = false, int weight = 0)
{
this.From = from;
this.To = to;
this.Weight = weight;
this.IsDirected = isDirected;
}
public int CompareTo(object obj)
{
if (obj is Edge)
{
var comparingTo = obj as Edge;
return this.Weight.CompareTo(comparingTo.Weight);
}
return 0; //TODO:what should we return?
}
}
public class AdjNode
{
public int EdgeWeight
{
get;
set;
}
public int Id
{
get;
set;
}
public AdjNode(int id)
{
this.Id = id;
this.EdgeWeight = 0;
}
public AdjNode(int id, int weight)
{
this.Id = id;
this.EdgeWeight = weight;
}
}
public class GraphAdj
{
public int V
{
get;
set;
}
public List<AdjNode>[] adj
{
get;
set;
}
public List<Edge> Edges
{
get;
set;
}
public GraphAdj(int v)
{
this.V = v;
this.adj = new List<AdjNode>[this.V];
for (int i = 0; i < this.V; i++)
{
this.adj[i] = new List<AdjNode>(); //allocate actual memory
}
this.Edges = new List<Edge>();
}
public void AddDirectedEdge(int from, int to)
{
adj[from].Add(new AdjNode(to));
this.Edges.Add(new Edge(from,to,true));
}
public void AddDirectedEdge(int from, int to, int weight)
{
adj[from].Add(new AdjNode(to,weight));
this.Edges.Add(new Edge(from, to, true, weight));
}
}
public string multiple(int A) {
int n = A;
GraphAdj directedGraphForNumber = new GraphAdj(n);
Queue<int> queueForNumbers = new Queue<int>();
string result = String.Empty;
bool[] visitedForNumbers = new bool[directedGraphForNumber.V];
int[] suffixes = new int[2] { 0, 1 };
//we will start from 1st node out of n node
queueForNumbers.Enqueue(1);
visitedForNumbers[1] = true;
while (true)
{
int from = queueForNumbers.Dequeue();
if (from == 0)
break;
for (int i = 0; i < suffixes.Length; i++)
{
int toNode = from * 10 + suffixes[i];
int reminder = toNode % n;
if (visitedForNumbers[reminder] == false)
{
visitedForNumbers[reminder] = true;
queueForNumbers.Enqueue(reminder);
directedGraphForNumber.AddDirectedEdge(from, reminder,suffixes[i]);
}
}
}
//Do BFS traversal with edges until zero th node encounters
bool[] visitedForBfs = new bool[directedGraphForNumber.V];
Queue<int> queueForBfs = new Queue<int>();
int[] parent = new int[directedGraphForNumber.V];
int source = 1;
visitedForBfs[source] = true;
queueForBfs.Enqueue(source);
parent[source] = -1;
while (queueForBfs.Count > 0)
{
int currentVertex = queueForBfs.Dequeue();
foreach (var adjacentVertex in directedGraphForNumber.adj[currentVertex])
{
if (visitedForBfs[adjacentVertex.Id] == false)
{
queueForBfs.Enqueue(adjacentVertex.Id);
parent[adjacentVertex.Id] = currentVertex;
visitedForBfs[adjacentVertex.Id] = true;
}
if (adjacentVertex.Id == 0) // we reach zero th node
{
queueForBfs.Clear(); //break out of bfs
}
}
}
//now time to find path all the way to start from zero using parent
List<int> pathListUsingParent = new List<int>();
int current = 0;
pathListUsingParent.Add(0); // add zero
while (current!=1)
{
pathListUsingParent.Add(parent[current]);
current = parent[current];
}
//reverse path to make number using edges
pathListUsingParent.Reverse();
result += "1"; //start node
//now read edges
for (int i = 0; i < pathListUsingParent.Count-1; i++)
{
int from = pathListUsingParent[i];
int to = pathListUsingParent[i + 1];
result += directedGraphForNumber.adj[from].FirstOrDefault(adj => adj.Id == to).EdgeWeight;
}
return result;
}
}

Answer 11

Here's a brute force version in Raku:
say (1..Inf).map( *.base(2) ).first( * %% $n );
The code generates a lazy (potentially infinite) sequence of candidate numbers and then searches for the first element that's divisible by n.
Being brute force it's not exceptionally fast, but the code is striking in its simplicity and expressiveness, as it is typical for Raku.