Constraint for binary linear model

Hi guys, If I have a 50x50 matrix of binary decision variables, is there a simple way to constrain the matrix so that only one row can become 1 and that the sum of columns=1?

Essentially I know that the answer can only appear in one row but I want all of the row to be used when the optimization occurs. Below is what I have to constrain it from only choosing a single positive integer from each column, now I want to ensure the single integers are in the same row.

x=zeros(50,50)
Ub=ones(50,50)
lb=x
a=ones(50,1)
Aeq=blkdiag(a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a,a);
beq=ones(1,50)

[Alan Weiss]

I am not sure that I understand your problem. It sounds like you want exactly one row to be entirely 1, and all the other rows entirely 0. Is that correct? Please let us know.

Alan Weiss

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