Reducing design variables in topology optimizations based on CMA-ES through spectral level set method

Abstract

Inthispaper, weattempttospeeduptopologyoptimizationbasedonCMA-ESbyusingthespectrallevelsetmethod (SLSM). Although CMA-ES provides robust topology optimization for design problems with intractable properties, it suffers from the curse of dimensionality. SLSM uses Fourier series expansion to generate level set functions to represent the boundary between structures and voids, which significantly reduces the number of design variables for topology optimization. We aim to use SLSM to speed up topology optimization with CMA-ES and evaluate it on several design problems.