A control system that distributes fluids from an injection to a production well at an adjustable rate has attracted considerable interest in recent years. Several optimization algorithms have been developed for this system and these techniques have proved to be beneficial in reservoir development. In this study, we propose a discrete optimization approach to increase oil production from thin oil rim reservoirs by smart horizontal wells under waterflooding. The smart well was equipped with several on-off control valves that can be adjusted to reach optimum oil production by maximize sweep efficiency and delay water breakthrough. This bring into optimization problem that involves discrete possible choices with valves settings as decision variables. We perform Binary Integer Programming (BIP) in order to decide valves settings in the injection and production well. BIP is one of linear programming problem where variable required being 0 or 1. These variables correspond with on-off control valves. Preliminary results obtained with this methodology show a significant improvement in the oil recovery factor, and the water saturation at breakthrough is observed to be more uniformly distributed across the reservoir, when compared with the reference non-optimized case. In the second stage of this study we add uncertainty in the geological description of the reservoir (permeability distribution), and perform robust optimization. To this end, we consider statistics of the Net Present Value (NPV) in the optimization objective function. We maximize an average of the NPV, and we control the risk attitude by means of a penalty term that involves the standard deviation of that quantity.