Sampling Design Method of Fast Optimal Latin Hypercube
In engineering design optimization, the optimal sampling design method is usually used to solve large-scale and complex system problems. A sampling design (FOLHD) method of fast optimal Latin hypercube is proposed in order to overcome the time-consuming and poor efficiency of the traditional optimal...
| Format: | Article |
|---|---|
| Language: | zho |
| Published: |
EDP Sciences
2019-08-01
|
| Series: | Xibei Gongye Daxue Xuebao |
| Subjects: | |
| Online Access: | https://www.jnwpu.org/articles/jnwpu/full_html/2019/04/jnwpu2019374p714/jnwpu2019374p714.html |
| Summary: | In engineering design optimization, the optimal sampling design method is usually used to solve large-scale and complex system problems. A sampling design (FOLHD) method of fast optimal Latin hypercube is proposed in order to overcome the time-consuming and poor efficiency of the traditional optimal sampling design methods. FOLHD algorithm is based on the inspiration that a near optimal large-scale Latin hypercube design can be established by a small-scale initial sample generated by using Successive Local Enumeration method and Translational Propagation algorithm. Moreover, a sampling resizing strategy is presented to generate samples with arbitrary size and owing good space-filling and projective properties. Comparing with the several existing sampling design methods, FOLHD is much more efficient in terms of the computation efficiency and sampling properties. |
|---|---|
| ISSN: | 1000-2758 2609-7125 |