Orthogonal Fractional Factorial Designs and in particular Orthogonal Arrays are frequently used in many fields of application, including medicine, engineering and agriculture. In this paper we present a methodology and an algorithm to find an orthogonal array, of given size and strength, that satisfies the generalized minimum aberration criterion. The methodology is based on the joint use of polynomial counting functions, complex coding of levels and algorithms for quadratic optimization and puts no restriction on the number of levels of each factor.

Generalized Minimum Aberration mixed-level orthogonal arrays: a general approach based on sequential integer quadratically constrained quadratic programming / Fontana, Roberto. - In: COMMUNICATIONS IN STATISTICS. THEORY AND METHODS. - ISSN 0361-0926. - STAMPA. - 46:9(2017), pp. 4275-4284. [10.1080/03610926.2015.1081947]

Generalized Minimum Aberration mixed-level orthogonal arrays: a general approach based on sequential integer quadratically constrained quadratic programming

FONTANA, ROBERTO
2017

Abstract

Orthogonal Fractional Factorial Designs and in particular Orthogonal Arrays are frequently used in many fields of application, including medicine, engineering and agriculture. In this paper we present a methodology and an algorithm to find an orthogonal array, of given size and strength, that satisfies the generalized minimum aberration criterion. The methodology is based on the joint use of polynomial counting functions, complex coding of levels and algorithms for quadratic optimization and puts no restriction on the number of levels of each factor.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2651221
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