Global optimization of the Saccharomyces cerevisiae: fermentation process

In this article, steady-state optimization of the Saccharomyces cerevisiae fermentation process problem is performed revealing the existence of multiple optimum solutions. The globally optimum solution was determined using the NEOS global optimization solver LINDO. A branch and bound strategy (bnb20.m) and the global search and multistart algorithms in the MATLAB global optimization toolbox were successful in determining locally optimum solutions and these results are validated by plotting the objective function against the decision variables. While in some cases all the strategies were successful in obtaining the globally optimum solutions, an example is presented where the most beneficial product value, which is not a stationary point and lies on the feasible boundary, is obtained by the LINDO global optimization solver (but not the other routines) as the globally optimum solution. The Jones-Kompala model was used to model the steady-state of the fermentation process. While several articles have been published demonstrating the existence of nonlinearities and bifurcations in this model, the challenges posed by this model to optimization has never been investigated so far and this work attempts to do so. Both dilution rate and the oxygen mass transfer coefficient were used as the decision variables individually and together.