Efficient and Robust Block Designs for Order-of-Addition Experiments
Chang-Yun Lin

TL;DR
This paper introduces a new, efficient method for designing robust block order-of-addition experiments using an expanded indicator function framework and orthogonal Latin squares, ensuring accurate effect estimation with manageable computational effort.
Contribution
It expands the indicator function framework for block OofA designs and develops algorithms utilizing orthogonal Latin squares to improve design robustness and computational efficiency.
Findings
Algorithms effectively manage confounding and aliasing.
Designs achieve power and error rates comparable to full designs.
Proposed method offers practical, efficient design construction.
Abstract
Designs for Order-of-Addition (OofA) experiments have received growing attention due to their impact on responses based on the sequence of component addition. In certain cases, these experiments involve heterogeneous groups of units, which necessitates the use of blocking to manage variation effects. Despite this, the exploration of block OofA designs remains limited in the literature. As experiments become increasingly complex, addressing this gap is essential to ensure that the designs accurately reflect the effects of the addition sequence and effectively handle the associated variability. Motivated by this, this paper seeks to address the gap by expanding the indicator function framework for block OofA designs. We propose the use of the word length pattern as a criterion for selecting robust block OofA designs. To improve search efficiency and reduce computational demands, we…
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Taxonomy
TopicsOptimal Experimental Design Methods · Statistical Methods in Clinical Trials · Advanced Multi-Objective Optimization Algorithms
