This paper proposes an automated search method for multidimensional design window (DW), which is defined as an area of satisfactory design solutions in a design parameter space, using both continuous evolutionary algorithms (CEA) and improved K-means clustering. This method consists of two phases : (a) CEA-based search for satisfactory design solutions in an ill-structured design space, and (b) clustering-based identification of DWs from the solutions. To demonstrate practical performance of the method, it is applied to an automated structural design of micro electrostatic actuator for optical memory.