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