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Combinations of Intelligent Methods and Applications pp 117–136Cite as

Hybrid Approach of Genetic Programming and Quantum-Behaved Particle Swarm Optimization for Modeling and Optimization of Fermentation Processes

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 23))

Abstract

This paper proposes a novel method for modeling and optimization of fermentation process with a hybrid approach of genetic programming (GP) and quantum-behaved particle swarm optimization (QPSO). In this method, the GP algorithm is first used to model the process, with the parameters of the model selected randomly within a given interval, while the population of models evolves. Then, the parameters of the model obtained by the GP are tuned by the QPSO algorithm in order to increase the fitting accuracy. Finally, the values of the independent variables of the model representing the culture conditions are optimized by the QPSO in order to maximize the dependent variable, which generally represents the yield of the fermentation product. The proposed method is applied to the fermentation process of the hyaluronic acid (HA) production by Streptococcus zooepidemicus. The experimental results show the efficiency of the GP-QPSO approach in the modeling and optimization of this fermentation process.

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Acknowledgments

This work is partially supported by the Natural Science Foundation of China (NSFC), under grant number 601190117 and 60975080, by the Program for New Century Excellent Talents in University, and by the Natural Science Foundation of Jiangsu Province, China (Project Number: BK2010143).

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Authors and Affiliations

  1. Key Laboratory of Advanced Control for Light Industry (Ministry of China), Jiangnan University, Wuxi, 214122, Jiangsu, China

    Jun Sun & Xiaojun Wu

  2. Department of Computer Science, University of Oxford, Wolfson Building, Parks Road, Oxford, OX1 3QD, UK

    Vasile Palade & Zhenyu Wang

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  1. Jun Sun
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  2. Vasile Palade
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  3. Zhenyu Wang
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  4. Xiaojun Wu
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Correspondence to Jun Sun .

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Editors and Affiliations

  1. School of Engineering, Dept. of Computer Engineering &, University of Patras, Patras, 26500, Greece

    Ioannis Hatzilygeroudis

  2. , Department of Computer Science, University of Oxford, Parks Road, Oxford, OX1 3QD, United Kingdom

    Vasile Palade

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Sun, J., Palade, V., Wang, Z., Wu, X. (2013). Hybrid Approach of Genetic Programming and Quantum-Behaved Particle Swarm Optimization for Modeling and Optimization of Fermentation Processes. In: Hatzilygeroudis, I., Palade, V. (eds) Combinations of Intelligent Methods and Applications. Smart Innovation, Systems and Technologies, vol 23. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36651-2_7

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  • DOI: https://doi.org/10.1007/978-3-642-36651-2_7

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  • Print ISBN: 978-3-642-36650-5

  • Online ISBN: 978-3-642-36651-2

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