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

TL;DR

This paper introduces a new methodology and algorithm for constructing generalized minimum aberration orthogonal arrays of specified size and strength, applicable to mixed-level factors without restrictions on levels.

Contribution

It presents a novel approach combining polynomial counting functions, complex coding, and quadratic optimization algorithms for flexible orthogonal array construction.

Findings

Successfully constructs orthogonal arrays with minimized aberration

Applicable to mixed-level factors with no restrictions on levels

Enhances design quality in various fields

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.