Research on improving parallel sequence sampling method in ship type optimization

Abstract

To solve the problem of complex and time-consuming simulation calculations in ship type optimization, the application of approximate model technology based on spatial segmentation sequence sampling is becoming increasingly widespread. Based on the Kriging approximation model and the cross-leaving one error method, a new sampling strategy is proposed during the iterative sampling process. The importance of adding sample subspaces and surrounding subspaces is considered in the design space, and parallel thinking is added to develop an efficient parallel sequence sampling method to improve sample aggregation. The proposed method was applied to optimize ship types, and its effectiveness was verified.