Sequential Design-Space Reduction and Its Application to Hull-Form Optimization

Abstract

Hull-form optimization is a complex engineering problem. Owing to the several numerical simulations and complex design-performance spaces, hull-form optimization is considered an inefficient process, which makes determining the global optimum difficult. This study used rough set theory (RST) to acquire knowledge and reduce the design space for hull-form optimization. Furthermore, we studied one of the hull-form optimization problems by practically applying RST to the appropriate number of sampling points. To solve this problem, we proposed the RST-based sequential design-space reduction (SDSR) method that uses interval theory to calculate subspace intersections and unions, as well as test calculations to choose an appropriate stopping criterion. Finally, SDSR was used to optimize a KRISO container ship to minimize the wave-making resistance. The results were compared to those of direct optimization and one-time design-space reduction, thus proving the feasibility of this method.