This paper presents a new Pareto-based coordinate exchange algorithm for populating or approximating the true Pareto front for multi-criteria optimal experimental design problems that arise naturally in a range of industrial applications. This heuristic combines an elitist-like operator inspired by evolutionary multi-objective optimization algorithms with a coordinate exchange operator that is commonly used to construct optimal designs. Benchmarking results from both a two-dimensional and three-dimensional example demonstrate that the proposed hybrid algorithm can generate highly reliable Pareto fronts with less computational effort than existing procedures in the statistics literature. The proposed algorithm also utilizes a multi-start operator, which makes it readily parallelizable for high performance computing infrastructures.
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The authors would like to thank Drs. Christine Anderson-Cook, Lu Lu and You-jin Park for sharing their examples. We also wish to express gratitude to the reviewers and editor who reviewed this work and allowed us the opportunity to improve the paper. The first author is also grateful to Dr. Nancy Flournoy for her valuable suggestions and comments.
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Cao, Y., Smucker, B.J. & Robinson, T.J. A hybrid elitist pareto-based coordinate exchange algorithm for constructing multi-criteria optimal experimental designs. Stat Comput 27, 423–437 (2017). https://doi.org/10.1007/s11222-016-9630-9
- Multi-criteria optimal experimental design
- Pareto front
- Hybrid algorithm