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5c241487aa
* rename Dynamic Programming -> dynamic_programming * rename dynamic-programming -> dynamic_programming
62 lines
1.5 KiB
C++
62 lines
1.5 KiB
C++
#include <iostream>
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#include <climits>
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using namespace std;
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#define MAX 10
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// dp table to store the solution for already computed sub problems
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int dp[MAX][MAX];
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// Function to find the most efficient way to multiply the given sequence of matrices
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int MatrixChainMultiplication(int dim[], int i, int j)
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{
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// base case: one matrix
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if (j <= i + 1)
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return 0;
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// stores minimum number of scalar multiplications (i.e., cost)
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// needed to compute the matrix M[i+1]...M[j] = M[i..j]
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int min = INT_MAX;
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// if dp[i][j] is not calculated (calculate it!!)
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if (dp[i][j] == 0)
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{
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// take the minimum over each possible position at which the
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// sequence of matrices can be split
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for (int k = i + 1; k <= j - 1; k++)
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{
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// recur for M[i+1]..M[k] to get a i x k matrix
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int cost = MatrixChainMultiplication(dim, i, k);
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// recur for M[k+1]..M[j] to get a k x j matrix
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cost += MatrixChainMultiplication(dim, k, j);
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// cost to multiply two (i x k) and (k x j) matrix
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cost += dim[i] * dim[k] * dim[j];
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if (cost < min)
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min = cost; // store the minimum cost
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}
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dp[i][j] = min;
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}
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// return min cost to multiply M[j+1]..M[j]
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return dp[i][j];
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}
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// main function
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int main()
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{
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// Matrix i has Dimensions dim[i-1] & dim[i] for i=1..n
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// input is 10 x 30 matrix, 30 x 5 matrix, 5 x 60 matrix
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int dim[] = {10, 30, 5, 60};
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int n = sizeof(dim) / sizeof(dim[0]);
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// Function Calling: MatrixChainMultiplications(dimensions_array, starting, ending);
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cout << "Minimum cost is " << MatrixChainMultiplication(dim, 0, n - 1) << "\n";
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return 0;
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} |