D- and I-optimal design of mixture experiments in the presence of ingredient availability constraints

Utami Syafitri, Bagus Sartono and Peter Goos ()

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

Abstract: Mixture experiments usually involve various constraints on the proportions of the ingredients of the mixture under study. In this paper, inspired by the fact that the available stock of certain ingredients is often limited, we focus on a new type of constraint, which we refer to as an ingredient availability constraint. This type of constraint substantially complicates the search for optimal designs for mixture experiments. One difficulty, for instance, is that the optimal number of experimental runs is not known a priori. We show that the optimal design problem in the presence of ingredient availability constraints is a nonlinear multidimensional knapsack problem and propose a variable neighborhood descent algorithm to identify D- and I-optimal designs for mixture experiments in case there is a limited stock of certain ingredients.

Keywords: Mixture experiment; Nonlinear multidimensional knapsack problem; D-optimality; I-optimality; Update formulas; Variable neighborhood descent algorithm; V-optimality (search for similar items in EconPapers)
Pages: 47 pages
Date: 2015-01
New Economics Papers: this item is included in nep-exp
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:ant:wpaper:2015003

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