解题思路
首先考虑最暴力的做法。对于每一步,我们都可以枚举每一条边,然后更新每两点之间经过(k)条边的最短路径。但是这样复杂度无法接受,我们考虑优化。
由于点数较少(其实最多只有(200)个点),(N)较大,考虑优化(N)。我们发现,其实可以直接从经过(i)条边的最短路和经过(j)条边的最短路推出经过(i+j)条边的最短路。这样的话,我们可以把每两点间的最短路保存下来,然后用类似于矩阵快速幂的做法就可以了。
最后为了不超时,我们需要将点的编号离散。最后时间复杂度是(O(T^3logN))。
参考程序
#include <cstdio>
#include <cstring>
#include <map>
#define LL long long
using namespace std;
const LL INF = 2147483647;
const LL MaxT = 110, MaxPoint = 210;
LL N, T, S, E;
LL Length[ MaxT ], I1[ MaxT ], I2[ MaxT ];
LL Num;
namespace myHash {
LL Reflection[ 1010 ];
map< LL, LL > Map;
void Hash() {
memset( Reflection, 0, sizeof( Reflection ) );
Map.clear();
for( LL i = 1; i <= T; ++i ) {
if( Map.find( I1[ i ] ) == Map.end() ) Map[ I1[ i ] ] = 1;
if( Map.find( I2[ i ] ) == Map.end() ) Map[ I2[ i ] ] = 1;
}
LL Last = 0;
for( map< LL, LL >::iterator it = Map.begin(); it != Map.end(); ++it )
Reflection[ ( *it ).first ] = ++Last;
Num = Last;
for( LL i = 1; i <= T; ++i ) {
I1[ i ] = Reflection[ I1[ i ] ];
I2[ i ] = Reflection[ I2[ i ] ];
}
return;
}
}//myHash
struct Matrix {
LL A[ MaxPoint ][ MaxPoint ];
void Clear() {
for( LL i = 1; i <= 200; ++i )
for( LL j = 1; j <= 200; ++j )
A[ i ][ j ] = INF;
return;
}
Matrix operator * ( const Matrix Other ) const {
Matrix Ans;
Ans.Clear();
for( LL i = 1; i <= Num; ++i )
for( LL j = 1; j <= Num; ++j )
for( LL k = 1; k <= Num; ++k )
Ans.A[ i ][ j ] = min( Ans.A[ i ][ j ], A[ i ][ k ] + Other.A[ k ][ j ] );
return Ans;
}
};
Matrix Basic, Ans;
void Init() {
Basic.Clear();
Ans.Clear();
for( int i = 1; i <= 200; ++i ) Ans.A[ i ][ i ] = 0;
for( int i = 1; i <= T; ++i ) {
Basic.A[ I1[ i ] ][ I2[ i ] ] = min( Basic.A[ I1[ i ] ][ I2[ i ] ], Length[ i ] );
Basic.A[ I2[ i ] ][ I1[ i ] ] = min( Basic.A[ I2[ i ] ][ I1[ i ] ], Length[ i ] );
}
return;
}
int main() {
scanf( "%lld%lld%lld%lld", &N, &T, &S, &E );
for( LL i = 1; i <= T; ++i )
scanf( "%lld%lld%lld", &Length[ i ], &I1[ i ], &I2[ i ] );
myHash::Hash();
Init();
for( ; N; N >>= 1, Basic = Basic * Basic )
if( N & 1 ) Ans = Basic * Ans;
printf( "%lld
", Ans.A[ myHash::Reflection[ S ] ][ myHash::Reflection[ E ] ] );
return 0;
}