The engineering optimization has been developed for the automatic design of engineering systems. Since the conventional optimum is determined without considering noise factors, applications to practical problems can be limited. Current design practice tends to account for these noises by the specification of closer tolerances or the use of safety factors. However, these approaches may be very expensive. Thus the consideration on the noises of design variables is needed for optimal design. A method is presented to find robust solutions for unconstrained optimization problems. The method is applied to discrete and continuous variables. The orthogonal array is utilized based on the Taguchi concept. Through mathematical proofs and numerical examples, it is verified that solutions from the suggested method are more insensitive than the conventional optimum within the range of variations for design variables.