Convex Optimization of Bioprocesses

We optimize a general model of bioprocesses, which is nonconvex due to the microbial growth in the biochemical reactors. We formulate a convex relaxation and give conditions guaranteeing its exactness in both the transient and steady-state cases. When the growth kinetics are modeled by the Contois or, under constant biomass, Monod or Powell functions, the relaxation is a second-order cone program, which can be solved efficiently at large scales. We implement the model on a numerical example based on a wastewater treatment system.

Automated summary

This paper optimizes a general model of bioprocesses and proposes a convex relaxation method to efficiently solve the problem of microbial growth in biochemical reactors. The feasibility and accuracy of the model are verified through numerical experiments.