Nonlinear-Optimization-on-fed-batch-reactor-system

This survey relates to using nonlinear optimization to improve or optimize fed-batch reactor system regarding the discussion in the academic journal presented “Optimization of fed-batch bioreactors using genetic algorithm: multiple control variables” by Debasis Sarkar and Jayant M. Modak, published in Computers & Chemical Engineering. Furthermore, the original article, “Optimal Production of Secreted Protein in Fed-Batch Reactors” by Seujeung Park and W. Fred Ramirez, published in AIChE Journal, Volume 34. Additionally, it should be acknowledged this report was produced for ISE 3210 (Nonlinear and Dynamic Optimization) at Ohio State University and is not meant for reproduction or publication.

Introduction

Fed-batch reactors use an operational technique in which bio-technological processes where one or more nutrients are fed to the bioreactor during cultivation and in which the product remain in the bioreactor until the end of the cycle. Optimal control of fed-batch reactors or bioreactors need to maximize the biomass and/or the metabolite production at the end of the cycle time.

Assignment Outline:

Select one real-world system that can be or has been optimized or improved using nonlinear optimization. Conduct a survey of any academic literature related to using nonlinear optimization to improve or optimize the system in question.

1. Prepare a report that summarizes your research. Your report does need to provide some technical details. At a minimum it should provide an outline of a model structure that can be used in said optimization or improvement. This model outline should be succinct, but provide enough detail so that someone who is familiar with nonlinear optimization, but not the particular application in question, can understand how the system is modeled. The outline of the model structure does not have to be given necessarily as a mathematical formulation.

2. Develop an AMPL or GAMS model that can solve an arbitrary instance of the nonlinear optimization application that you surveyed in Problem 1. To do so, you should provide first a succinct model formulation. The model formulation may be a simplification of models appearing in the literature that you survey. Second, you should develop AMPL or GAMS code that can solve an arbitrary instance of the problem (i.e., with any sensible set of problem data). Finally, you should provide required problem data for a small but non-trivial instance of the problem and a summary of the solution and solution time for the problem instance. A suite of optimization solvers that can be used at no cost to solve your problem are available at https://neos-server.org/neos/