|
Title
|
|
|
|
An iterated local search algorithm for the construction of large scale D-optimal experimental designs
| |
|
Author
|
|
|
|
| |
|
Abstract
|
|
|
|
| We focus on the D-optimal design of screening experiments involving main-eects regression models, especially with large numbers of factors and observations. We propose a new selection strategy for the coordinate-exchange algorithm based on an orthogonality measure of the design. Computational exper- iments show that this strategy nds better designs within an execution time that is 30% shorter than other strategies. We also provide strong evidence that the use of the prediction variance as a selection strategy does not provide any added value in comparison to simpler selection strategies. Additionally, we propose a new iterated local search algorithm for the construction of D-optimal experimental designs. This new algorithm clearly outperforms the original coordinate-exchange algorithm. |
| |
|
Language
|
|
|
|
English
| |
|
Source (series)
|
|
|
|
Research paper / University of Antwerp, Faculty of Applied Economics ; 2013:006
| |
|
Publication
|
|
|
|
Antwerp
:
UA
,
2013
| |
|
Volume/pages
|
|
|
|
20 p.
| |
|
Full text (open access)
|
|
|
|
| |
|