An Improved Geometric Programming Approach for Optimization of Biochemical Systems

This paper proposes an improved geometric programming approach to address the optimization of biochemical systems. In the proposed method we take advantage of a special and interesting class of nonlinear kinetic models known as generalized mass action (GMA) models. In most situations optimization pr...

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Bibliographic Details
Published in:Journal of Applied Mathematics 2014-01, Vol.2014 (2014), p.951-960-690
Main Authors: Xu, Gongxian, Wang, Lei
Format: Article
Language:English
Subjects:
Biochemistry
Chemical research
Computational efficiency
Equivalence
Heuristic
Mathematical models
Mathematical optimization
Methods
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Optimization
Programming
Strategy
Stress
Transformations
Vitamin E
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Summary:This paper proposes an improved geometric programming approach to address the optimization of biochemical systems. In the proposed method we take advantage of a special and interesting class of nonlinear kinetic models known as generalized mass action (GMA) models. In most situations optimization problems with GMA models are nonconvex and difficult problems to solve for global optimality. To deal with this difficulty, in this work, some transformation strategy is first used to convert the optimization problem with GMA models into an equivalent problem. Then a convexification technique is applied to transform this resulting optimization problem into a series of standard geometric programming problems that can be solved to reach a global solution. Two case studies are presented to demonstrate the advantages of the proposed method in terms of computational efficiency.
ISSN:1110-757X
1687-0042
DOI:10.1155/2014/719496