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Defect avoidance methods are likely to play a key role in overcoming the challenge of mask blank detectivity in extreme ultraviolet (EUV) lithography. In this work, we propose an innovative EUV mask defect avoidance method. It is the first approach that allows exploring all the degrees of freedom available for defect avoidance (pattern shift, rotation and mask floorplanning). We model the defect avoidance problem as a global, nonconvex optimization problem and then solve it using a combination of random walk and gradient descent. For a 8-nm polysilicon layer of an ARM Cortex M0 layout, our method achieves a 60% point better mask yield compared to prior art in defect avoidance for a 40-defect mask. We show that pattern shift is the most significant degree of freedom for improving mask yield. Rotation and mask floorplanning can also help improve mask yield to a Certain extent. [ABSTRACT FROM AUTHOR]