2-D linear optimisation problem

I am trying to solve 2D optmisation problem in which my variable ranges from x(1,1) to x(4,4) and this variable should be either 0 or 1. When I am solving an equation for example 1.2x(1,1)+5.3x(2,3) I am always getting a zero for this solution if I bound my variable by ub 1 and lb 0. Can anyone tell me what is the way to get the optimal solution?

[Walter Roberson]

All zeros is the correct optimization for 1.2x(1,1)+5.3x(2,3), as all-zeros gives an output of 0, which cannot be improved on because you have no subtractions.

Are you possibly looking for a maxima instead of for a minima? If you are, then optimize the negative of the expression.

[Dee]

No I have to minimise it but the coefficients given to be are like this whereas the variables are in binary form only

[Bjorn Gustavsson]

Because it would be the smallest possible value you can get? If you let me rewrite this as:

f = 1.2*y+5.3*z

...and we then constrain y and z to be between 0 and 1 the smallest possible value of f will be for y and z equal to zero. For this type of problem pen (pencil) and paper and a think about the meaning of ∇ is more useful than matlab.