期刊
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
卷 46, 期 10, 页码 1780-1789出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207721.2013.835003
关键词
optimum Latin hypercube sampling; simulated annealing; space filling quality; design of experiment; sequencing optimisation
类别
资金
- Royal Golden Jubilee PhD Programme [PHD/0041/2551]
- Thailand Research Fund [RSA5280006]
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.
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