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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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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