Multiobjective optimization and nonlinear model predictive control of the continuous fermentation process involving Saccharomyces Cerevisiae

Abstract

In the debate between two accomplished researchers David Pimentel and Bruce Dale about the use of ethanol as fuel, one of the most contentious issues is whether or not the carbon dioxide that is released in to the atmosphere during the fermentation process contributes significantly to global warming. While it does not appear that either side would give in to the other, there can be no doubt that the release of carbon dioxide into the atmosphere is not desirable and should be restricted as much as possible. The aim of this work is to use multiobjective optimization to optimize the fermentation process and maximize the production of ethanol while minimizing the release of carbon dioxide into the atmosphere. The minimization of the carbon dioxide released into the atmosphere is equivalent to minimizing the respiratory coefficient. In this paper, multiobjective optimization techniques are used to compute the Pareto optimal profiles for the continuous fermentation process problem involving Saccharomyces Cerevisiae. State of the art local (CONOPT and DICOPT) and global solvers (BARON and ANTIGONE) available in the NEOS server are used and it is demonstrated that it is imperative to use a global optimization strategy to calculate the most beneficial solution profiles.

Keywords:

• Fermentation
• optimization
• bioreactor
• pareto curve
• dilution rate
• mass transfer