A variable-neighbourhood search algorithm for finding optimal run orders in the presence of serial correlation and time trends

Jean-Jacques Garroi, Peter Goos () and Kenneth Sörensen

Working Papers from University of Antwerp, Faculty of Business and Economics

Abstract: The responses obtained from response surface designs that are run sequentially often exhibit serial correlation or time trends. The order in which the runs of the design are performed then has an impact on the precision of the parameter estimators. This article proposes the use of a variable-neighbourhood search algorithm to compute run orders that guarantee a precise estimation of the effects of the experimental factors. The importance of using good run orders is demonstrated by seeking D-optimal run orders for a central composite design in the presence of an AR(1) autocorrelation pattern.

Keywords: AR(1); Autocorrelation; Central composite design; D-optimality criterion; Local search (search for similar items in EconPapers)
Pages: 24 pages
Date: 2006-10
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:ant:wpaper:2006026

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