Well placement optimization is the process to search for the optimal operating conditions of infill wells for improving recovery. Infill drilling is expected to generate the additional revenue, but requires an enormous initial investment. This study determines the optimal number of injection wells and their locations in waterflooding project. Multi-objective genetic algorithm based on non-dominated sorting and crowding distance sorting is adapted to find Pareto-solutions which minimize the cost and maximize the revenue simultaneously. Non-dominated sorting guarantees the convergence and crowding distance sorting maintains the diversity of Pareto-solutions. The result shows that the suggested approach can obtain production scenarios of good quality satisfying given objectives successfully.