最原始的01背包问题:
Solution01: 自顶向下,记忆化搜索
class Knapsack01{
private:
vector<vector<int>> memo;
int bestValue(const vector<int> &w, const vector<int> &v, int index, int c){
if ( index < 0 || c <= 0 )
return 0;
if ( memo[index][c] != -1)
return memo[index][c];
int res = bestValue(w, v, index-1, c);
if( c >= w[index] )
res = max(res, v[index] + bestValue(w, v, index-1, c-w[index]));
memo[index][c] = res;
return res;
}
public:
int knapsack01(const vector<int> &w, const vector<int> &v, int C){
int n = w.size();
memo = vector<vector<int>>(n, vector<int>(C+1, -1));
return bestValue(w, v, n-1, C);
}
};
Solution02: 自底向上 动态规划
class Knapsack01{
public:
int knapsack01(const vector<int> &w, const vector<int> &v, int C){
assert( w.size() == v.size() );
int n = w.size();
if ( n==0 )
return 0;
vector<vector<int>> memo(n, vector<int>(C+1, -1));
for ( int j = 0; j <= C; j++ ){
memo[0][j] = ( j >= w[0] ? v[0] : 0);
}
for (int i = 1; i < n; i++) {
for (int j = 0; j <= C ; j++) {
memo[i][j] = memo[i-1][j];
if ( j >= w[i] )
memo[i][j] = max( memo[i][j], v[i] + memo[i-1][j-w[i]]);
}
}
return memo[n-1][C];
}
};
总结: 定义状态和状态转移