High efficient sequential maximin latin hypercube design method

Abstract

The invention relates to a sequential maximin latin hypercube design method, belonging to the technical field of engineering optimization design. Through adoption of the method, the purpose that a user uniformly increases m2 sample points in an n-dimensional design space with m1 already existing sample points is achieved. According to the method, firstly, the m1 already existing sample points are mapped into an m<n> orthogonal super checkerboard through methods of mesh generation and mesh mapping; and then, sequential sample points are gradually generated according to a Maximin criterion through a local enumeration method, and the spatial uniform distribution and projection uniformity of newly increased sample points and already existing sample points are guaranteed. According to the sequential maximin latin hypercube design method, the positions of already existing sample points are considered in generation of the sample points, so that the spatial uniform distribution and projection uniformity of all sample points are guaranteed. If being applied to a dynamic agent model, the method can remarkably improve the global optimization ability and optimization efficiency of an optimization design method of the dynamic agent model; and the method is applicable to the modern engineering design optimization field using high precise analysis models.

Description

technical field [0001] The invention relates to a high-efficiency sequential Latin hypercube test design method, which belongs to the technical field of engineering optimization design. Background technique [0002] Nowadays, many engineering design problems are becoming more and more complex. In order to improve the analysis accuracy and reliability, many high-precision analysis models are widely used in engineering design. While improving the analysis accuracy and reliability, the high-precision analysis model also brings the difficulty of time-consuming calculation. Although today's computer software and hardware technology has made great progress, it is still extremely time-consuming to call a high-precision analysis model to complete an analysis. In addition, modern engineering design problems often involve multiple coupled disciplines. For example, aircraft design involves disciplines such as aerodynamics, structure, power, stealth, and control. Various disciplines i...

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Problems solved by technology

However, the Quasi-LHD method needs to call the optimization process in the process of generating new sample points, which greatly increases the time-consuming of experimental design, and cannot guarantee that the new sample points have better spatial uniformity.

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