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|Title:||Multi-objective optimization of glycopeptide antibiotic production in batch and fed batch processes|
|Keywords:||Sorting Genetic Algorithm|
|Publisher:||ELSEVIER SCI LTD|
|Abstract:||Fermentation optimization involves potentially conflicting multiple objectives such as product concentration and production media cost. Simultaneous optimization of these objectives would result in a multiobjective optimization problem, which is characterized by a set of multiple solutions, knows as pareto optimal solutions. These solutions gives flexibility in evaluating the trade-offs and selecting the most suitable operating policy. Here, epsilon-constraint approach was used to generate the pareto solutions for two objectives: product concentration and product per unit cost of media, for batch and fed batch operations using process model for Amycolatopsis balhimycina, a glycopeptide antibiotic producer. This resulted in a set of several pareto optimal solutions with the two objectives ranging from (0.75 g l(-1) 3.97 g $(-1)) to (0.44 g l(-1), 5.19 g $(-1)) for batch and from (1.5 g l(-1) 5.46 g $(-1)) to (1.1 g l(-1), 6.34 g $(-1)) for fed batch operations. One pareto solution each for batch and for fed batch mode was experimentally validated. (C) 2011 Elsevier Ltd. All rights reserved.|
|Appears in Collections:||Article|
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