Abstract
In this investigation the InterCriteria Analysis (ICrA) approach is applied. The apparatuses of index matrices and intuitionistic fuzzy sets are at the core of ICrA. They are used to examine the influences of two main genetic algorithms (GA) parameters—the rates of crossover (xovr) and mutation (mutr). A series of parameter identification procedures for S. cerevisiae and E. coli fermentation process models is fulfilled. Twenty GA with different xovr and mutr values are applied. Relations between ICrA criteria—GA parameters and outcomes, on the one hand, and fermentation process model parameters, on the other hand, are investigated. The ICrA approach is applied by pairs, as well as by triples. The obtained results are thoroughly analysed towards computation time and model accuracy and some conclusions about the derived criteria interactions are reported.
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References
Angelova, M.: Modified genetic algorithms and intuitionistic fuzzy logic for parameter identification of fed-batch cultivation Model. Ph.D. Thesis. Sofia (2014) (in Bulgarian)
Angelova, M., Tzonkov, St., Pencheva, T.: Modified multi-population genetic algorithm for yeast fed-batch cultivation parameter identification. Int. J. Bioautomation 13(4), 163–172 (2009)
Atanassov, K.: A new topological operator over intuitionistic fuzzy sets. Notes Intuit. Fuzzy Sets 21(3), 90–92 (2015)
Atanassov, K.: Generalized index matrices. Compt. rend. Acad. Bulg. Sci. 40(11), 15–18 (1987)
Atanassov, K.: Index Matrices: Towards an Augmented Matrix Calculus. Springer International Publishing, Switzerland (2014)
Atanassov, K.: On Intuitionistic Fuzzy Sets Theory. Springer, Berlin (2012)
Atanassov, K.: On index matrices, part 1: standard cases. Adv. Stud. Contemp. Math. 20(2), 291–302 (2010)
Atanassov, K.: On index matrices, part 2: intuitionistic fuzzy case. Proc. Jangjeon Math. Soc. 13(2), 121–126 (2010)
Atanassov, K.: On index matrices. part 5: 3-dimensional index matrices. Adv. Stud. Contemp. Math. 24(4), 423–432 (2014)
Atanassov, K., Atanassova, V., Gluhchev, G.: InterCriteria analysis: ideas and problems. Notes Intuit. Fuzzy Sets 21(1), 81–88 (2015)
Atanassov, K., Mavrov, D., Atanassova, V.: Intercriteria decision making: a new approach for multicriteria decision making, based on index matrices and intuitionistic fuzzy sets. Issues Intuit. Fuzzy Sets Gen. Nets 11, 1–8 (2014)
Atanassov, K., Szmidt, E., Kacprzyk, J.: On intuitionistic fuzzy pairs. Notes Intuit. Fuzzy Sets 19(3), 1–13 (2013)
Bastin, G., Dochain, D.: On-line Estimation and Adaptive Control of Bioreactors. Elsevier Scientific Publications, Amsterdam (1991)
Boussaid, I., Lepagnot, J., Siarry, P.: A survey on optimization metaheuristics. Inf. Sci. 237, 82–117 (2013)
Dickinson, R.J., Schweizer, M.: Metabolism and Molecular Physiology of Saccharomyces cerevisiae, 2nd edn. CRC Press, Florida (2004)
Goldberg, D.E.: Genetic algorithms in search, optimization and machine learning. Addison Wesley Longman, London (2006)
Lin, W., Lee, W., Hong, T.: Adapting crossover and mutation rates in genetic algorithms. J. Inf. Sci. Eng. 19, 889–903 (2003)
Matsuoka, Y., Shimizu, K.: Importance of understanding the main metabolic regulation in response to the specific pathway mutation for metabolic engineering of Escherichia coli. Comput. Struct. Biotechnol. J. 3(4), e201210018 (2012)
Obitko, M.: Genetic Algorithms, http://www.obitko.com/tutorials/genetic-algorithms/
Pencheva, T., Angelova, M., Atanassova, V., Roeva, O.: InterCriteria analysis of genetic algorithm parameters in parameter identification. Notes Intuit. Fuzzy Sets 21(2), 99–110 (2015)
Pencheva, T., Hristozov, I., Huell, D., Hitzmann, B., Tzonkov, St.: Modelling of functional states during Saccharomyces cerevisiae fed-batch cultivation. Int. J. Bioautomation 2, 8–16 (2005)
Roeva, O., Pencheva, T., Hitzmann, B., Tzonkov, St.: A genetic algorithms based approach for identification of Escherichia coli fed-batch fermentation. Int. J. Bioautomation 1, 30–41 (2004)
Roeva, O., Fidanova, S.: Chapter 13. Application of genetic algorithms and ant colony optimization for modeling of E. coli cultivation process, In: Real-World Application of Genetic Algorithms. In Tech (2012)
Roeva, O.: Sensitivity analysis of E. coli fed-batch cultivation local models. Mathematica Balkanica. New Series 25(4), 395–411 (2011)
Vassilev, P., Todorova, L., Andonov, V.: An auxiliary technique for InterCriteria Analysis via a three dimensional index matrix. Notes Intuit. Fuzzy Sets 21(2), 71–76 (2015)
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The work is supported by the Bulgarian National Scientific Fund under the grant DFNI-I-02-5 “InterCriteria Analysis—A New Approach to Decision Making”.
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Roeva, O., Pencheva, T., Angelova, M., Vassilev, P. (2016). InterCriteria Analysis by Pairs and Triples of Genetic Algorithms Application for Models Identification. In: Fidanova, S. (eds) Recent Advances in Computational Optimization. Studies in Computational Intelligence, vol 655. Springer, Cham. https://doi.org/10.1007/978-3-319-40132-4_12
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DOI: https://doi.org/10.1007/978-3-319-40132-4_12
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