The present research propose optimization methods that are robust in the sense that they produce\ud solutions insensitive to changes in the input parameters: these optimization methods are known\ud as Robust Design Techniques. The need for Robust Design method appears in many contests:\ud during the preliminary design process, the exact value of some input parameters is not known,\ud consequently the aim is try to look for a solution as less dependent on the unknown input parameters\ud as possible. The concept of robust optimization is demonstrated by using a 2-D airfoil shape\ud optimization problem. It has been observed  that minimizing drag at a single design point has\ud unintended consequences at nearby off-design points. Hicks and Vanderplaats demonstrate that\ud a direct optimization approach that minimizes drag at one mach number (e.g., M=0,75) actually\ud increases drag at nearby Mach number (e.g., M=0,70). To avoid this consequence the airfoil drag\ud minimization problem could be faced by means of an inverse optimization approach but the final\ud result could be almost the same of the single point design . The conclusion is that the latter\ud techniques produce solutions that perform well in correspondence of the design point but have\ud poor off-design characteristic
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