Although I’m not an ANSYS user, I do use optimization. Some definitions might be useful if you are new to optimization:
Objective function: The thing you want to minimize (or maximize). This is usually a single thing, and for structures is most often weight. If only a single material is involved, minimizing volume is the same as minimizing weight. For a beam of a single material and constant length, minimizing the cross-sectional area is the same as minimizing weight.
Design variables: The things you will allow to vary to meet the objective. There can be many of these and they are usually things like area, thickness, location, dimensions, etc. You should put upper and lower bounds on the values of these to keep them within realistic limits.
Constraints: The things you want to put limits on, such as stress, deflection, vibration frequency, buckling load, etc. You should be sure to include all the important criteria in your problem. If you only put limits on deflection, for example, the result may (or probably will) exceed some other criteria, such as stress, unless you put a constraint on stress as well.
Although I don't totally understand your problem, I do not think you should try to “minimize” the deflection. As the deflection goes to zero, the weight of the part will go to infinity! There must be some small value of deflection you are willing to allow, and that should be the “constraint” not the “objective”. Weight should be the objective, since that is a measure of how efficiently you are keeping the deflection down.
You should be careful about constraining the deflection of a single point. The optimizer might meet your requirement at that point, but exceed it elsewhere, so you may have to constrain several points. If you are talking about keeping the hole circular within a certain tolerance, then you are talking about the “relative deflection” of the points around the hole. Is buckling a possibility in your problem?
You should probably constrain some stresses as well, or at least check the stresses in the final result. If you have too many design variables and/or constraints, it will get bogged down numerically, so you must understand your problem well enough to know what’s important and what’s not. The “optimum” will be a “local” rather than a “global” optimum. It’s the closet optimum found near your starting point, so if you don’t like the results, you could try again starting with different initial values of the design variables.