Name
Title | ||
|---|---|---|
An efficient optimum Latin hypercube sampling technique based on sequencing optimisation using simulated annealing |
Abstract | ||
|---|---|---|
This paper proposes a new optimal Latin hypercube sampling method OLHS for design of a computer experiment. The new method is based on solving sequencing and continuous optimisation using simulated annealing. There are two sets of design variables used in the optimisation process: sequencing and real number variables. The special mutation operator is developed to deal with such design variables. The performance of the proposed numerical strategy is tested and compared with three established OLHS methods, namely genetic algorithm GA, enhanced stochastic evolutionary algorithm ESEA and successive local enumeration SLE. Based on 30 test problems with various design dimensions and numbers of sampling points, the proposed method gives the best results. The method can generate an optimum set of sampling points within reasonable computing time; therefore, it can be considered as a powerful tool for design of computer experiments. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1080/00207721.2013.835003 | International Journal of Systems Science |
Keywords | DocType | Volume |
design of experiment,simulated annealing | Journal | 46 |
Issue | ISSN | Citations |
10 | 0020-7721 | 3 |
PageRank | References | Authors |
0.38 | 9 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nantiwat Pholdee | 1 | 39 | 8.08 |
| Sujin Bureerat | 2 | 64 | 11.36 |