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Parameter Estimation of the Kinetic \(\alpha \)-Pinene Isomerization Model Using the MCSFilter Algorithm

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Computational Science and Its Applications – ICCSA 2018 (ICCSA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10961))

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Abstract

This paper aims to illustrate the application of a derivative-free multistart algorithm with coordinate search filter, designated as the MCSFilter algorithm. The problem used in this study is the parameter estimation problem of the kinetic \(\alpha \)-pinene isomerization model. This is a well known nonlinear optimization problem (NLP) that has been investigated as a case study for performance testing of most derivative based methods proposed in the literature. Since the MCSFilter algorithm features a stochastic component, it was run ten times to solve the NLP problem. The optimization problem was successfully solved in all the runs and the optimal solution demonstrates that the MCSFilter provides a good quality solution.

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Author information

Authors and Affiliations

  1. CIEPQPF, Department of Chemical Engineering, Faculty of Sciences and Technology, University of Coimbra, 3030-790, Coimbra, Portugal

    Andreia Amador, Lino O. Santos & Andrey Romanenko

  2. Research Centre in Digitalization and Intelligent Robotics (CeDRI), Instituto Politécnico de Bragança, 5300-253, Bragança, Portugal

    Florbela P. Fernandes

  3. Ciengis, SA, Rua Pedro Nunes, Ed.E, Coimbra, Portugal

    Andrey Romanenko

  4. Algoritmi Research Centre, University of Minho, 4710-057, Braga, Portugal

    Ana Maria A. C. Rocha

Authors
  1. Andreia Amador
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  2. Florbela P. Fernandes
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  3. Lino O. Santos
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  4. Andrey Romanenko
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  5. Ana Maria A. C. Rocha
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Corresponding author

Correspondence to Florbela P. Fernandes .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka shi, Fukuoka, Japan

    Bernady O. Apduhan

  9. Politecnico di Bari, Bari, Italy

    Eufemia Tarantino

  10. Myongji University, Yongin, Korea (Republic of)

    Yeonseung Ryu

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Amador, A., Fernandes, F.P., Santos, L.O., Romanenko, A., Rocha, A.M.A.C. (2018). Parameter Estimation of the Kinetic \(\alpha \)-Pinene Isomerization Model Using the MCSFilter Algorithm. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10961. Springer, Cham. https://doi.org/10.1007/978-3-319-95165-2_44

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  • DOI: https://doi.org/10.1007/978-3-319-95165-2_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95164-5

  • Online ISBN: 978-3-319-95165-2

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