Not feasible answer

1

Hello,

I am trying to solve an optimization problem, it seems it is convex, However, the CVX gives not feasible answer. I do not know where is the problem.

cvx_begin quiet
variables t r(7,1) c(7,1) z
maximize (z)
subject to
for iGroup = 1:nGroups
c(iGroup)+r(iGroup,1)>=z;
for iUser=1:2NoUserperGroup
1-sum(c(1:7,1))>=(1-t)a(iGroup,iUser)+tb(iGroup,iUser)+c-2sqrt(1-t)d(iGroup,iUser;
1-r(iGroup)>=e(iGroup,iUser)+tf(iGroup,iUser)-2*sqrt(t)*g(iGroup,iUser);
end
end
t>=0;
t<=1;
for i=1:7
c(i,1)>=0;
r(i,1)>=0;
end
cvx_end

Thanks

2

You show us a program, without the input data, and without the solver or CVX output. What do you expect us to do?

Don’t use quiet until your program is working well. By not using quiet, the solver and CVX output will be printed to the screen…

All but section 1 of https://yalmip.github.io/debugginginfeasible apply to diagnosing CVX programs which report (primal) infeasible.