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An algorithm for generating efficient block designs via a novel particle swarm approach

Author

Listed:
  • Saeid Pooladsaz

    (Isfahan University of Technology)

  • Mahboobeh Doosti-Irani

    (Isfahan University of Technology)

Abstract

The problem of finding optimal block designs can be formulated as a combinatorial optimization, but its resolution is still a formidable challenge. This paper presents a general and user-friendly algorithm, namely Modified Particle Swarm Optimization (MPSO), to construct optimal or near-optimal block designs. It can be used for several classes of block designs such as binary, non-binary and test-control block designs with correlated or uncorrelated observations. In order to evaluate the algorithm, we compare our results with the optimal designs presented in some published papers. An advantage of our algorithm is its independency to the sizes of blocks and the structure of correlations.

Suggested Citation

  • Saeid Pooladsaz & Mahboobeh Doosti-Irani, 2024. "An algorithm for generating efficient block designs via a novel particle swarm approach," Computational Statistics, Springer, vol. 39(5), pages 2437-2449, July.
    • Handle: RePEc:spr:compst:v:39:y:2024:i:5:d:10.1007_s00180-023-01369-x
    DOI: 10.1007/s00180-023-01369-x
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    References listed on IDEAS

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    1. Weng Kee Wong & Ray-Bing Chen & Chien-Chih Huang & Weichung Wang, 2015. "A Modified Particle Swarm Optimization Technique for Finding Optimal Designs for Mixture Models," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-23, June.
    2. Khodsiani, R. & Pooladsaz, S., 2017. "Universal optimal block designs under hub correlation structure," Statistics & Probability Letters, Elsevier, vol. 129(C), pages 387-392.
    3. 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.
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