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Journal Articles Journal of Process Control Year : 2022

Fitting second-order cone constraints to microbial growth data

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Abstract

Second-order cone programming is a highly tractable convex optimization class. In this paper, we fit general second-order cone constraints to data. This is of use when one must solve large-scale, nonlinear optimization problems, but modeling is either impractical or does not lead to second-order cone or otherwise tractable constraints. Our motivating application is biochemical process optimization, in which we seek to fit second-order cone constraints to microbial growth data. The fitting problem is nonconvex. We solve it using the concave-convex procedure, which takes the form of a sequence of second-order cone programs. We validate our approach on simulated and experimental microbial growth data, and compare its performance with conventional nonlinear least-squares fitting.
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Dates and versions

hal-03766997 , version 1 (01-09-2022)

Licence

Attribution - NonCommercial - NoDerivatives - CC BY 4.0

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Shuyao Tan, Emna Krichen, Alain Rapaport, Elodie Passeport, Joshua Taylor. Fitting second-order cone constraints to microbial growth data. Journal of Process Control, 2022, 118, pp.165-169. ⟨10.1016/j.jprocont.2022.08.018⟩. ⟨hal-03766997⟩
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