model: sets: ten/1..10/:y; four/1..4/; score(ten,four):a,x; endsets max=@sum(score(i,j):x(i,j)*a(i,j)); @for(score(i,j):x(i,j)>=y(i)); @sum(ten(i):y(i))=4; @for(four(j):@sum(ten(i):x(i,j))<=6); @for(ten(i):@sum(four(j):(1-y(i))*x(i,j))<=3); @for(ten:@bin(y)); @for(score:@bin(x)); M=@sum(score(i,j):x(i,j)*a(i,j)); data: a=8.4 8.4 9.1 8.7 9.3 8.4 8.4 8.9 8.4 8.1 8.4 9.5 8.1 8.7 9.0 8.4 8.4 9.0 8.3 9.4 9.4 8.7 8.5 8.4 9.5 8.4 8.3 8.4 8.4 8.8 8.7 8.2 8.4 8.4 8.4 9.3 9.0 8.1 8.2 9.1; enddata end 帮我改写成matlab代码
时间: 2023-10-21 22:03:32 浏览: 52
以下是将该模型转换为Matlab代码的过程:
```matlab
% sets
ten = 1:10;
four = 1:4;
% parameters
a = [8.4 8.4 9.1 8.7 9.3 8.4 8.4 8.9 8.4 8.1;
8.4 8.4 9.5 8.1 8.7 9.0 8.4 8.4 9.0 8.3;
9.4 8.7 8.5 8.4 9.5 8.4 8.3 8.4 8.8 8.7;
8.2 8.4 8.4 8.4 9.3 9.0 8.1 8.2 9.1 0];
% variables
y = optimvar('y', ten, 'Type', 'integer', 'LowerBound', 0, 'UpperBound', 1);
x = optimvar('x', ten, four, 'Type', 'integer', 'LowerBound', 0, 'UpperBound', 1);
% objective function
M = sum(sum(a .* x));
% constraints
constr = [sum(y) == 4;
sum(x, 1) <= 6;
sum((1-y) .* x, 2) <= 3;
x >= y;
x <= y .* 10000];
% problem
prob = optimproblem('Objective', M, 'Constraints', constr);
% solve
[sol, fval] = solve(prob);
```
注意:由于该模型中存在二进制变量,所以需要使用优化工具箱中的`optimvar`函数来定义变量类型。同时,由于Matlab中的矩阵索引从1开始,而GAMS中是从0开始,所以在对参数进行赋值时需要将索引减去1。