You are given a bag of size W kg and you are provided costs of packets different weights of oranges in array cost[] where cost[i] is basically the cost of ‘i’ kg packet of oranges. Where cost[i] = -1 means that ‘i’ kg packet of orange is unavailable
Find the minimum total cost to buy exactly W kg oranges and if it is not possible to buy exactly W kg oranges then print -1. It may be assumed that there is an infinite supply of all available packet types.
Note: array starts from index 1.
Examples:
Input : W = 5, cost[] = {20, 10, 4, 50, 100}
Output : 14
We can choose two oranges to minimize cost. First
orange of 2Kg and cost 10. Second orange of 3Kg
and cost 4.
Input : W = 5, cost[] = {1, 10, 4, 50, 100}
Output : 5
We can choose five oranges of weight 1 kg.
Input : W = 5, cost[] = {1, 2, 3, 4, 5}
Output : 5
Costs of 1, 2, 3, 4 and 5 kg packets are 1, 2, 3,
4 and 5 Rs respectively.
We choose packet of 5kg having cost 5 for minimum
cost to get 5Kg oranges.
Input : W = 5, cost[] = {-1, -1, 4, 5, -1}
Output : -1
Packets of size 1, 2 and 5 kg are unavailable
because they have cost -1. Cost of 3 kg packet
is 4 Rs and of 4 kg is 5 Rs. Here we have only
weights 3 and 4 so by using these two we can
not make exactly W kg weight, therefore answer
is -1.
Method 1:
This problem is can be reduced to Unbounded Knapsack. So in the cost array, we first ignore those packets which are not available i.e; cost is -1 and then traverse the cost array and create two array val[] for storing the cost of ‘i’ kg packet of orange and wt[] for storing weight of the corresponding packet. Suppose cost[i] = 50 so the weight of the packet will be i and the cost will be 50.
Algorithm :
- Create matrix min_cost[n+1][W+1], where n is number of distinct weighted packets of orange and W is the maximum capacity of the bag.
- Initialize the 0th row with INF (infinity) and 0th Column with 0.
- Now fill the matrix
- if wt[i-1] > j then min_cost[i][j] = min_cost[i-1][j] ;
- if wt[i-1] <= j then min_cost[i][j] = min(min_cost[i-1][j], val[i-1] + min_cost[i][j-wt[i-1]]);
- If min_cost[n][W]==INF then output will be -1 because this means that we cant not make weight W by using these weights else output will be min_cost[n][W].
Below is the implementation of the above algorithm:
C++
#include<bits/stdc++.h>
#define INF 1000000
using namespace std;
int MinimumCost( int cost[], int n, int W)
{
vector< int > val, wt;
int size = 0;
for ( int i=0; i<n; i++)
{
if (cost[i]!= -1)
{
val.push_back(cost[i]);
wt.push_back(i+1);
size++;
}
}
n = size;
int min_cost[n+1][W+1];
for ( int i=0; i<=W; i++)
min_cost[0][i] = INF;
for ( int i=1; i<=n; i++)
min_cost[i][0] = 0;
for ( int i=1; i<=n; i++)
{
for ( int j=1; j<=W; j++)
{
if (wt[i-1] > j)
min_cost[i][j] = min_cost[i-1][j];
else
min_cost[i][j] = min(min_cost[i-1][j],
min_cost[i][j-wt[i-1]] + val[i-1]);
}
}
return (min_cost[n][W]==INF)? -1: min_cost[n][W];
}
int main()
{
int cost[] = {1, 2, 3, 4, 5}, W = 5;
int n = sizeof (cost)/ sizeof (cost[0]);
cout << MinimumCost(cost, n, W);
return 0;
}
|
Java
import java.util.*;
class GFG {
public static int MinimumCost( int cost[], int n,
int W)
{
Vector<Integer> val = new Vector<Integer>();
Vector<Integer> wt = new Vector<Integer>();
int size = 0 ;
for ( int i = 0 ; i < n; i++)
{
if (cost[i] != - 1 )
{
val.add(cost[i]);
wt.add(i + 1 );
size++;
}
}
n = size;
int min_cost[][] = new int [n+ 1 ][W+ 1 ];
for ( int i = 0 ; i <= W; i++)
min_cost[ 0 ][i] = Integer.MAX_VALUE;
for ( int i = 1 ; i <= n; i++)
min_cost[i][ 0 ] = 0 ;
for ( int i = 1 ; i <= n; i++)
{
for ( int j = 1 ; j <= W; j++)
{
if (wt.get(i- 1 ) > j)
min_cost[i][j] = min_cost[i- 1 ][j];
else
min_cost[i][j] = Math.min(min_cost[i- 1 ][j],
min_cost[i][j-wt.get(i- 1 )] +
val.get(i- 1 ));
}
}
return (min_cost[n][W] == Integer.MAX_VALUE)? - 1 :
min_cost[n][W];
}
public static void main(String[] args)
{
int cost[] = { 1 , 2 , 3 , 4 , 5 }, W = 5 ;
int n = cost.length;
System.out.println(MinimumCost(cost, n, W));
}
}
|
Python3
INF = 1000000
def MinimumCost(cost, n, W):
val = list ()
wt = list ()
size = 0
for i in range (n):
if (cost[i] ! = - 1 ):
val.append(cost[i])
wt.append(i + 1 )
size + = 1
n = size
min_cost = [[ 0 for i in range (W + 1 )] for j in range (n + 1 )]
for i in range (W + 1 ):
min_cost[ 0 ][i] = INF
for i in range ( 1 , n + 1 ):
min_cost[i][ 0 ] = 0
for i in range ( 1 , n + 1 ):
for j in range ( 1 , W + 1 ):
if (wt[i - 1 ] > j):
min_cost[i][j] = min_cost[i - 1 ][j]
else :
min_cost[i][j] = min (min_cost[i - 1 ][j],
min_cost[i][j - wt[i - 1 ]] + val[i - 1 ])
if (min_cost[n][W] = = INF):
return - 1
else :
return min_cost[n][W]
cost = [ 1 , 2 , 3 , 4 , 5 ]
W = 5
n = len (cost)
print (MinimumCost(cost, n, W))
|
C#
using System;
using System.Collections.Generic;
class GFG {
public static int MinimumCost( int []cost, int n,
int W)
{
List< int > val = new List< int >();
List< int > wt = new List< int >();
int size = 0;
for ( int i = 0; i < n; i++)
{
if (cost[i] != -1)
{
val.Add(cost[i]);
wt.Add(i + 1);
size++;
}
}
n = size;
int [,]min_cost = new int [n+1,W+1];
for ( int i = 0; i <= W; i++)
min_cost[0,i] = int .MaxValue;
for ( int i = 1; i <= n; i++)
min_cost[i,0] = 0;
for ( int i = 1; i <= n; i++)
{
for ( int j = 1; j <= W; j++)
{
if (wt[i-1] > j)
min_cost[i,j] = min_cost[i-1,j];
else
min_cost[i,j] = Math.Min(min_cost[i-1,j],
min_cost[i,j-wt[i-1]] + val[i-1]);
}
}
return (min_cost[n,W] == int .MaxValue )? -1: min_cost[n,W];
}
public static void Main()
{
int []cost = {1, 2, 3, 4, 5};
int W = 5;
int n = cost.Length;
Console.WriteLine(MinimumCost(cost, n, W));
}
}
|
PHP
<?php
$INF = 1000000;
function MinimumCost(& $cost , $n , $W )
{
global $INF ;
$val = array ();
$wt = array ();
$size = 0;
for ( $i = 0; $i < $n ; $i ++)
{
if ( $cost [ $i ] != -1)
{
array_push ( $val , $cost [ $i ]);
array_push ( $wt , $i + 1);
$size ++;
}
}
$n = $size ;
$min_cost = array_fill (0, $n + 1,
array_fill (0, $W + 1, NULL));
for ( $i = 0; $i <= $W ; $i ++)
$min_cost [0][ $i ] = $INF ;
for ( $i = 1; $i <= $n ; $i ++)
$min_cost [ $i ][0] = 0;
for ( $i = 1; $i <= $n ; $i ++)
{
for ( $j = 1; $j <= $W ; $j ++)
{
if ( $wt [ $i - 1] > $j )
$min_cost [ $i ][ $j ] = $min_cost [ $i - 1][ $j ];
else
$min_cost [ $i ][ $j ] = min( $min_cost [ $i - 1][ $j ],
$min_cost [ $i ][ $j - $wt [ $i - 1]] +
$val [ $i - 1]);
}
}
if ( $min_cost [ $n ][ $W ] == $INF )
return -1;
else
return $min_cost [ $n ][ $W ];
}
$cost = array (1, 2, 3, 4, 5);
$W = 5;
$n = sizeof( $cost );
echo MinimumCost( $cost , $n , $W );
?>
|
Javascript
<script>
let INF = 1000000;
function MinimumCost(cost, n, W)
{
let val = [], wt = [];
let size = 0;
for (let i=0; i<n; i++)
{
if (cost[i]!= -1)
{
val.push(cost[i]);
wt.push(i+1);
size++;
}
}
n = size;
let min_cost = new Array(n+1);
for (let i = 0; i < n + 1; i++)
{
min_cost[i] = new Array(W + 1);
}
for (let i=0; i<=W; i++)
min_cost[0][i] = INF;
for (let i=1; i<=n; i++)
min_cost[i][0] = 0;
for (let i=1; i<=n; i++)
{
for (let j=1; j<=W; j++)
{
if (wt[i-1] > j)
min_cost[i][j] = min_cost[i-1][j];
else
min_cost[i][j] = Math.min(min_cost[i-1][j],
min_cost[i][j-wt[i-1]] + val[i-1]);
}
}
return (min_cost[n][W]==INF)? -1: min_cost[n][W];
}
let cost = [1, 2, 3, 4, 5], W = 5;
let n = cost.length;
document.write(MinimumCost(cost, n, W));
</script>
|
Time Complexity: O(N*W)
Auxiliary Space: O(N*W)
Space Optimized Solution If we take a closer look at this problem, we may notice that this is a variation of Rod Cutting Problem. Instead of doing maximization, here we need to do minimization.
C++
#include<bits/stdc++.h>
using namespace std;
int minCost( int cost[], int n)
{
int dp[n+1];
dp[0] = 0;
for ( int i = 1; i<=n; i++)
{
int min_cost = INT_MAX;
for ( int j = 0; j < i; j++)
if (cost[j]!=-1)
min_cost = min(min_cost, cost[j] + dp[i-j-1]);
dp[i] = min_cost;
}
return dp[n];
}
int main()
{
int cost[] = {20, 10, 4, 50, 100};
int W = sizeof (cost)/ sizeof (cost[0]);
cout << minCost(cost, W);
return 0;
}
|
Java
import java.util.*;
class Main
{
public static int minCost( int cost[], int n)
{
int dp[] = new int [n + 1 ];
dp[ 0 ] = 0 ;
for ( int i = 1 ; i <= n; i++)
{
int min_cost = Integer.MAX_VALUE;
for ( int j = 0 ; j < i; j++)
if (cost[j]!=- 1 ) {
min_cost = Math.min(min_cost, cost[j] + dp[i - j - 1 ]);
}
dp[i] = min_cost;
}
return dp[n];
}
public static void main(String[] args) {
int cost[] = { 10 ,- 1 ,- 1 ,- 1 ,- 1 };
int W = cost.length;
System.out.print(minCost(cost, W));
}
}
|
Python3
import sys
def minCost(cost, n):
dp = [ 0 for i in range (n + 1 )]
for i in range ( 1 , n + 1 ):
min_cost = sys.maxsize
for j in range (i):
if cost[j]! = - 1 :
min_cost = min (min_cost,
cost[j] + dp[i - j - 1 ])
dp[i] = min_cost
return dp[n]
cost = [ 10 , - 1 , - 1 , - 1 , - 1 ]
W = len (cost)
print (minCost(cost, W))
|
C#
using System;
class GFG {
static int minCost( int [] cost, int n)
{
int [] dp = new int [n + 1];
dp[0] = 0;
for ( int i = 1; i <= n; i++)
{
int min_cost = Int32.MaxValue;
for ( int j = 0; j < i; j++)
if (cost[j]!=-1)
min_cost = Math.Min(min_cost,
cost[j] + dp[i - j - 1]);
dp[i] = min_cost;
}
return dp[n];
}
static void Main() {
int [] cost = {20, 10, 4, 50, 100};
int W = cost.Length;
Console.Write(minCost(cost, W));
}
}
|
Javascript
<script>
function minCost(cost, n)
{
let dp = new Array(n+1);
dp[0] = 0;
for (let i = 1; i<=n; i++)
{
let min_cost = Number.MAX_VALUE;
for (let j = 0; j < i; j++)
if (j < n)
min_cost = Math.min(min_cost, cost[j] + dp[i-j-1]);
dp[i] = min_cost;
}
return dp[n];
}
let cost = [20, 10, 4, 50, 100];
let W = cost.length;
document.write(minCost(cost, W));
</script>
|
Time Complexity: O(N2)
Auxiliary Space: O(N)
Top Down Approach: We can also solve the problem using memoization.
C++
#include <bits/stdc++.h>
using namespace std;
int helper(vector< int >& cost, vector< int >& weight, int n,
int w, vector<vector< int > >& dp)
{
if (w == 0)
return 0;
if (w < 0 or n <= 0)
return INT_MAX;
if (dp[n][w] != -1)
return dp[n][w];
if (cost[n - 1] < 0)
return dp[n][w]
= min(INT_MAX,
helper(cost, weight, n - 1, w, dp));
if (weight[n - 1] <= w) {
return dp[n][w]
= min(cost[n - 1]
+ helper(cost, weight, n,
w - weight[n - 1], dp),
helper(cost, weight, n - 1, w, dp));
}
return dp[n][w] = helper(cost, weight, n - 1, w, dp);
}
int minCost(vector< int >& cost, int W)
{
int N = cost.size();
vector< int > weight(N);
for ( int i = 1; i <= N; i++) {
weight[i - 1] = i;
}
vector<vector< int > > dp(N + 1, vector< int >(W + 1, -1));
int res = helper(cost, weight, N, W, dp);
return (res == INT_MAX) ? -1 : res;
}
int main()
{
vector< int > cost = { 20, 10, 4, 50, 100 };
int W = cost.size();
cout << minCost(cost, W);
return 0;
}
|
Java
import java.io.*;
class GFG {
public static int helper( int cost[], int weight[],
int n, int w, int dp[][])
{
if (w == 0 )
return 0 ;
if (w < 0 || n <= 0 )
return Integer.MAX_VALUE;
if (dp[n][w] != - 1 )
return dp[n][w];
if (cost[n - 1 ] < 0 )
return dp[n][w] = Math.min(
Integer.MAX_VALUE,
helper(cost, weight, n - 1 , w, dp));
if (weight[n - 1 ] <= w) {
return dp[n][w] = Math.min(
cost[n - 1 ]
+ helper(cost, weight, n,
w - weight[n - 1 ], dp),
helper(cost, weight, n - 1 , w, dp));
}
return dp[n][w]
= helper(cost, weight, n - 1 , w, dp);
}
public static int minCost( int cost[], int W)
{
int N = cost.length;
int weight[] = new int [N];
for ( int i = 1 ; i <= N; i++) {
weight[i - 1 ] = i;
}
int dp[][] = new int [N + 1 ][W + 1 ];
for ( int i = 0 ; i < N + 1 ; i++)
for ( int j = 0 ; j < W + 1 ; j++)
dp[i][j] = - 1 ;
int res = helper(cost, weight, N, W, dp);
return (res == Integer.MAX_VALUE) ? - 1 : res;
}
public static void main(String[] args)
{
int cost[] = { 20 , 10 , 4 , 50 , 100 };
int W = cost.length;
System.out.print(minCost(cost, W));
}
}
|
Python3
import sys
def helper(cost, weight, n, w, dp):
if (w = = 0 ):
return 0
if (w < 0 or n < = 0 ):
return sys.maxsize
if (dp[n][w] ! = - 1 ):
return dp[n][w]
if (cost[n - 1 ] < 0 ):
dp[n][w] = min (sys.maxsize, helper(cost, weight, n - 1 , w, dp))
return dp[n][w]
if (weight[n - 1 ] < = w):
dp[n][w] = min (cost[n - 1 ] + helper(cost, weight, n, w - weight[n - 1 ], dp), helper(cost, weight, n - 1 , w, dp))
return dp[n][w]
dp[n][w] = helper(cost, weight, n - 1 , w, dp)
return dp[n][w]
def minCost(cost, W):
N = len (cost)
weight = [ 0 for i in range (N)]
for i in range ( 1 ,N + 1 ):
weight[i - 1 ] = i
dp = [[ - 1 for i in range (W + 1 )] for j in range (N + 1 )]
res = helper(cost, weight, N, W, dp)
return - 1 if (res = = sys.maxsize) else res
cost = [ 20 , 10 , 4 , 50 , 100 ]
W = len (cost)
print (minCost(cost, W))
|
C#
using System;
class GFG
{
static int helper( int [] cost, int [] weight,
int n, int w, int [,] dp)
{
if (w == 0)
return 0;
if (w < 0 || n <= 0)
return Int32.MaxValue;
if (dp[n,w] != -1)
return dp[n,w];
if (cost[n - 1] < 0)
return dp[n,w] = Math.Min(
Int32.MaxValue,
helper(cost, weight, n - 1, w, dp));
if (weight[n - 1] <= w)
{
return dp[n,w] = Math.Min(
cost[n - 1]
+ helper(cost, weight, n,
w - weight[n - 1], dp),
helper(cost, weight, n - 1, w, dp));
}
return dp[n,w]
= helper(cost, weight, n - 1, w, dp);
}
static int minCost( int [] cost, int W)
{
int N = cost.Length;
int [] weight = new int [N];
for ( int i = 1; i <= N; i++)
{
weight[i - 1] = i;
}
int [,] dp = new int [N + 1, W + 1];
for ( int i = 0; i < N + 1; i++)
for ( int j = 0; j < W + 1; j++)
dp[i,j] = -1;
int res = helper(cost, weight, N, W, dp);
return (res == Int32.MaxValue) ? -1 : res;
}
static public void Main()
{
int [] cost = { 20, 10, 4, 50, 100 };
int W = cost.Length;
Console.Write(minCost(cost, W));
}
}
|
Javascript
<script>
function helper(cost, weight, n, w, dp)
{
if (w == 0)
return 0;
if (w < 0 || n <= 0)
return Number.MAX_VALUE;
if (dp[n][w] != -1)
return dp[n][w];
if (cost[n - 1] < 0)
return dp[n][w]
= Math.min(Number.MAX_VALUE,
helper(cost, weight, n - 1, w, dp));
if (weight[n - 1] <= w) {
return dp[n][w]
= Math.min(cost[n - 1]
+ helper(cost, weight, n,
w - weight[n - 1], dp),
helper(cost, weight, n - 1, w, dp));
}
return dp[n][w] = helper(cost, weight, n - 1, w, dp);
}
function minCost(cost,W)
{
let N = cost.length;
let weight = new Array(N);
for (let i = 1; i <= N; i++) {
weight[i - 1] = i;
}
let dp = new Array(N + 1).fill(-1).map(()=> new Array(W + 1).fill(-1));
let res = helper(cost, weight, N, W, dp);
return (res == Number.MAX_VALUE) ? -1 : res;
}
let cost = [ 20, 10, 4, 50, 100 ];
let W = cost.length;
document.write(minCost(cost, W), "</br>" );
</script>
|
Time Complexity: O(N*W)
Auxiliary Space: O(N*W)
This article is contributed by Shashank Mishra ( Gullu ).This article is reviewed by team GeeksForGeeks.
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.