442 - Matrix Chain Multiplication

本文介绍了一种通过合理安排矩阵乘法顺序来减少计算所需的乘法次数的方法。文章提供了一个具体的例子,展示了不同的矩阵乘法顺序如何显著影响计算效率,并附带了实现这一优化的示例代码。

Suppose you haveto evaluate an expression like A*B*C*D*E where A,B,C,D and E are matrices.Since matrix multiplication is associative, the order in which multiplicationsare performed is arbitrary. However, the number of elementary multiplicationsneeded strongly depends on the evaluation order you choose.

For example, let Abe a 50*10 matrix, B a 10*20 matrix and C a 20*5 matrix. There are twodifferent strategies to compute A*B*C, namely (A*B)*C and A*(B*C).

The first onetakes 15000 elementary multiplications, but the second one only 3500.

Your job is towrite a program that determines the number of elementary multiplications neededfor a given evaluation strategy.

Input Specification

Input consists oftwo parts: a list of matrices and a list of expressions.

The first line ofthe input file contains one integer n (  ), representingthe number of matrices in the first part. The next n lineseach contain one capital letter, specifying the name of the matrix, and twointegers, specifying the number of rows and columns of the matrix.

The second part ofthe input file strictly adheres to the following syntax (given in EBNF):

Second Part = Line{ Line } <EOF>

Line       = Expression <CR>

Expression =Matrix | "(" Expression Expression ")"

Matrix     = "A" | "B" |"C" | ... | "X" | "Y" | "Z"

Output Specification

For each expressionfound in the second part of the input file, print one line containing the word"error" if evaluation of the expression leads to an error due tonon-matching matrices. Otherwise print one line containing the number ofelementary multiplications needed to evaluate the expression in the wayspecified by the parentheses.

Sample Input

9

A 50 10

B 10 20

C 20 5

D 30 35

E 35 15

F 15 5

G 5 10

H 10 20

I 20 25

A

B

C

(AA)

(AB)

(AC)

(A(BC))

((AB)C )

(((((DE)F)G)H)I)

(D(E(F(G(HI)))))

((D(EF))((GH)I))

Sample Output

0

0

0

error

10000

error

3500

15000

40500

47500

15125

代码:

#include<cstdio>

#include<stack>

#include<iostream>

#include<string>

using namespace std;

 

struct Matrix

{

    int a, b;

    Matrix(int a=0,int b=0):a(a),b(b) {}

} m[26];

 

stack<Matrix> s;

 

int main()

{

    int n;

    cin >> n;

    for(int i = 0; i < n; i++)

    {

        string name;

        cin >> name;

        int k = name[0] - 'A';

        cin >> m[k].a >> m[k].b;

    }

   

    string expr;

    while(cin >> expr)

    {

        int len = expr.length();

        bool error = false;

        int ans = 0;

        for(int i = 0; i < len; i++)

        {

            if(isalpha(expr[i]))

            {

                s.push(m[expr[i] - 'A']);

            }

            else if(expr[i] == ')')

            {

                Matrix m2 = s.top();

                s.pop();

                Matrix m1 = s.top();

                s.pop();

                if(m1.b != m2.a)

                {

                    error = true;

                    break;

                }

                ans += m1.a * m1.b * m2.b;

                s.push(Matrix(m1.a, m2.b));

            }

        }

        if(error)

        {

            printf("error\n");

        }

        else

        {

            printf("%d\n", ans);

        }

    }

    return 0;

}

import cvxpy as cp import numpy as np import pandas as pd data = pd.read_excel('附件1.xlsx') X = data.iloc[1:, 1:2] Y = data.iloc[1:, 2:3] W = data.iloc[2:, 3:4] # 收集点垃圾量(i=1..n) xi = X.values.flatten() # 转换为一维数组 (n,) yi = Y.values.flatten() # 转换为一维数组 (n,) wi = W.values.flatten() # 转换为一维数组 (n,) # 定义参数 n = 30 # 收集点数量(i=1..n,0为处理厂) K = 30 # 车辆总数 Q = 5 # 最大载重 # 计算距离矩阵dij(i,j=0..n) dij = np.zeros((n+1, n+1)) for i in range(n+1): for j in range(n+1): dij[i, j] = np.sqrt((xi[i] - xi[j])**2 + (yi[i] - yi[j])**2) x = cp.Variable((n+1, n+1, K), boolean=True) # x_ijv: 车辆v从i到j y = cp.Variable((n, K), boolean=True) # y_iv: 车辆v服务收集点i(i=1..n,索引0..n-1) z = cp.Variable(K, boolean=True) # z_v: 使用车辆v u = cp.Variable((n+1, K), nonneg=True) # u_iv: 车辆v访问i后的累计载重(i=0..n,u[0,v]=0) objective = cp.Minimize(cp.sum(cp.sum(cp.sum(dij @ x, axis=2), axis=1), axis=0)) # 约束条件 constraints = [] # 1. 每个收集点被 exactly 一辆车服务(i=1..n,对应y的索引0..n-1) for i in range(n): constraints.append(cp.sum(y[i, :]) == 1) # 2. 流量守恒(i=1..n,处理厂i=0的约束在6中) for i in range(1, n+1): # 收集点i(1..n,y索引i-1) for v in range(K): constraints.append(cp.sum(x[i, :, v]) == y[i-1, v]) # 离开i的次数等于服务i的次数 constraints.append(cp.sum(x[:, i, v]) == y[i-1, v]) # 进入i的次数等于服务i的次数 # 3. 载重约束 for v in range(K): constraints.append(cp.sum(wi * y[:, v]) <= Q * z[v]) # 4. MTZ约束(子回路消除) for v in range(K): constraints.append(u[0, v] == 0) # 处理厂出发时载重为0 for i in range(1, n+1): # 收集点i(1..n,wi[i-1]) constraints.append(u[i, v] >= wi[i-1]) # 载重下限 constraints.append(u[i, v] <= Q) # 载重上限 for j in range(1, n+1): if i != j: constraints.append(u[i, v] - u[j, v] + Q * x[i, j, v] <= Q - wi[j-1]) # 5. 车辆使用约束:服务收集点则使用车辆 for i in range(n): for v in range(K): constraints.append(y[i, v] <= z[v]) # 6. 出发返回约束(处理厂i=0,出发到收集点1..n,返回从收集点1..n到0) for v in range(K): constraints.append(cp.sum(x[0, 1:, v]) == z[v]) # 出发次数等于车辆使用 constraints.append(cp.sum(x[1:, 0, v]) == z[v]) # 返回次数等于车辆使用 # 建立问题并求解 problem = cp.Problem(objective, constraints) problem.solve() # 输出结果(示例,需根据实际需求处理) print("最优目标值:", problem.value) print("使用的车辆:", z.value)D:\python\python.exe D:\35433\Documents\数模练习\电工杯\问题1.py D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 1 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 2 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 3 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 4 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 5 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 6 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 7 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 8 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 9 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 10 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 11 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 12 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 13 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 14 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 15 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 16 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 17 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 18 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 19 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 20 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 21 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 22 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 23 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 24 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 25 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 26 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 27 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 28 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 29 times so far. D:\python\Lib\site-packages\cvxpy\expressions\expression.py:674: UserWarning: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. Use ``*`` for matrix-scalar and vector-scalar multiplication. Use ``@`` for matrix-matrix and matrix-vector multiplication. Use ``multiply`` for elementwise multiplication. This code path has been hit 30 times so far. D:\python\Lib\site-packages\cvxpy\reductions\solvers\solving_chain_utils.py:41: UserWarning: The problem has an expression with dimension greater than 2. Defaulting to the SCIPY backend for canonicalization.
05-25
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