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A more accurate second-order polynomial metamodel using a pseudo-random number assignment strategy

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  • M Chih

    (Chung-Shan Institute of Science and Technology, Taoyuan, Taiwan)

Abstract

The response surface metamodel is a useful sequential methodology for approximating the relationship between the input variables and the output response in computer simulation. Several strategies have been proposed to increase the accuracy of the estimation of the metamodel. In the current paper, we introduce an effective pseudo-random number (PRN) assignment strategy with Box-Behnken design to construct a more accurate second-order polynomial metamodel to estimate the network reliability of a complex system. The results obtained from the simulation approach show that the reduction in maximum absolute relative error between the response surface approximation and the actual reliability function is 35.63% after the PRN assignment strategy is applied.

Suggested Citation

  • M Chih, 2013. "A more accurate second-order polynomial metamodel using a pseudo-random number assignment strategy," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(2), pages 198-207, February.
  • Handle: RePEc:pal:jorsoc:v:64:y:2013:i:2:p:198-207
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    Cited by:

    1. Jack P. C. Kleijnen, 2015. "Response Surface Methodology," International Series in Operations Research & Management Science, in: Michael C Fu (ed.), Handbook of Simulation Optimization, edition 127, chapter 0, pages 81-104, Springer.
    2. Chih, Mingchang, 2023. "Stochastic stability analysis of particle swarm optimization with pseudo random number assignment strategy," European Journal of Operational Research, Elsevier, vol. 305(2), pages 562-593.

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