IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i11p2538-d1161219.html
   My bibliography  Save this article

Constructing Optimal Designs for Order-of-Addition Experiments Using a Hybrid Algorithm

Author

Listed:
  • Dongying Wang

    (School of Statistics, Jilin University of Finance and Economics, Changchun 130117, China)

  • Sumin Wang

    (Center for Combinatorics, LPMC & KLMDASR, Nankai University, Tianjin 300071, China)

Abstract

For order-of-addition experiments, the response is affected by the addition order of the experimental materials. Consequently, the main interest focuses on creating a predictive model and an optimal design for optimizing the response. Van Nostrand proposed the pairwise-order (PWO) model for detecting PWO effects. Under the PWO model, the full PWO design is optimal under various criteria but is often unaffordable because of the large run size. In this paper, we consider the D -, A - and M . S . -optimal fractional PWO designs. We first present some results on information matrices. Then, a flexible and efficient algorithm is given for generating these optimal PWO designs. Numerical simulation shows that the generated design has an appealing efficiency in comparison with the full PWO design, though with only a small fraction of runs. Several comparisons with existing designs illustrate that the generated designs achieve better efficiencies, and the best PWO designs and some selected 100% efficient PWO designs generated by the new algorithm are reported.

Suggested Citation

  • Dongying Wang & Sumin Wang, 2023. "Constructing Optimal Designs for Order-of-Addition Experiments Using a Hybrid Algorithm," Mathematics, MDPI, vol. 11(11), pages 1-20, May.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:11:p:2538-:d:1161219
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/11/2538/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/11/2538/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yuna Zhao & Dennis K. J. Lin & Min-Qian Liu, 2021. "Designs for order-of-addition experiments," Journal of Applied Statistics, Taylor & Francis Journals, vol. 48(8), pages 1475-1495, June.
    2. Chen, Ray-Bing & Hsu, Yen-Wen & Hung, Ying & Wang, Weichung, 2014. "Discrete particle swarm optimization for constructing uniform design on irregular regions," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 282-297.
    3. Zhao, Yuna & Lin, Dennis K.J. & Liu, Min-Qian, 2022. "Optimal designs for order-of-addition experiments," Computational Statistics & Data Analysis, Elsevier, vol. 165(C).
    4. Nguyen, Nam-Ky & Miller, Alan J., 1992. "A review of some exchange algorithms for constructing discrete D-optimal designs," Computational Statistics & Data Analysis, Elsevier, vol. 14(4), pages 489-498, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Arnouts, Heidi & Goos, Peter, 2010. "Update formulas for split-plot and block designs," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3381-3391, December.
    2. Guo, Bing & Chen, Xueping & Wang, Xiaodi, 2024. "Component projection balanced designs for order of addition experiments," Statistics & Probability Letters, Elsevier, vol. 211(C).
    3. Fewell, Jason E. & Bergtold, Jason S. & Williams, Jeffery R., 2016. "Farmers' willingness to contract switchgrass as a cellulosic bioenergy crop in Kansas," Energy Economics, Elsevier, vol. 55(C), pages 292-302.
    4. Bergtold, Jason S. & Shanoyan, Aleksan & Fewell, Jason E. & Williams, Jeffery R., 2017. "Annual bioenergy crops for biofuels production: Farmers' contractual preferences for producing sweet sorghum," Energy, Elsevier, vol. 119(C), pages 724-731.
    5. Nguyen, Nam-Ky & Liu, Min-Qian, 2008. "An algorithmic approach to constructing mixed-level orthogonal and near-orthogonal arrays," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5269-5276, August.
    6. Godolphin, J.D. & Warren, H.R., 2014. "An efficient procedure for the avoidance of disconnected incomplete block designs," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1134-1146.
    7. Sung Jung, Joo & Jin Yum, Bong, 1996. "Construction of exact D-optimal designs by tabu search," Computational Statistics & Data Analysis, Elsevier, vol. 21(2), pages 181-191, February.
    8. Xiao, Qian & Xu, Hongquan, 2021. "A mapping-based universal Kriging model for order-of-addition experiments in drug combination studies," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    9. Rios, Nicholas & Winker, Peter & Lin, Dennis K.J., 2022. "TA algorithms for D-optimal OofA Mixture designs," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
    10. Stephen J. Walsh & John J. Borkowski, 2022. "Improved G -Optimal Designs for Small Exact Response Surface Scenarios: Fast and Efficient Generation via Particle Swarm Optimization," Mathematics, MDPI, vol. 10(22), pages 1-17, November.
    11. Moein Saleh & Ming-Hung Kao & Rong Pan, 2017. "Design D-optimal event-related functional magnetic resonance imaging experiments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(1), pages 73-91, January.
    12. CUERVO, Daniel Palhazi & GOOS, Peter & SÖRENSEN, Kenneth, 2013. "An iterated local search algorithm for the construction of large scale D-optimal experimental designs," Working Papers 2013006, University of Antwerp, Faculty of Business and Economics.
    13. Szu Hui Ng & Stephen E. Chick, 2004. "Design of follow‐up experiments for improving model discrimination and parameter estimation," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(8), pages 1129-1148, December.
    14. Zhao, Yuna & Lin, Dennis K.J. & Liu, Min-Qian, 2022. "Optimal designs for order-of-addition experiments," Computational Statistics & Data Analysis, Elsevier, vol. 165(C).
    15. Shengli Zhao & Zehui Dong & Yuna Zhao, 2022. "Order-of-Addition Orthogonal Arrays with High Strength," Mathematics, MDPI, vol. 10(7), pages 1-17, April.
    16. García-Ródenas, Ricardo & García-García, José Carlos & López-Fidalgo, Jesús & Martín-Baos, José Ángel & Wong, Weng Kee, 2020. "A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    17. Kassie, Girma T. & Abdulai, Awudu & Haile, Aynalem & Yitayih, Mulugeta & Asnake, Woinishet & Rischkowsky, Barbara, 2023. "Understanding pastoralists’ preferences for goat traits: Application of all-levels and end-point choice experiments," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 104(C).
    18. Zabihinia Gerdroodbari, Yasin & Khorasany, Mohsen & Razzaghi, Reza & Heidari, Rahmat, 2024. "Management of prosumers using dynamic export limits and shared Community Energy Storage," Applied Energy, Elsevier, vol. 355(C).
    19. Wang, Xiaodi & Huang, Hengzhen, 2023. "Group symmetric Latin hypercube designs for symmetrical global sensitivity analysis," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    20. Ahmed Selema & Mohamed N. Ibrahim & Peter Sergeant, 2022. "Metal Additive Manufacturing for Electrical Machines: Technology Review and Latest Advancements," Energies, MDPI, vol. 15(3), pages 1-18, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:11:y:2023:i:11:p:2538-:d:1161219. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.