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Volume 11
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10.3390/pr11020427
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Article

Multi-Population Genetic Algorithm and Cuckoo Search Hybrid Technique for Parameter Identification of Fermentation Process Models

by
Maria Angelova
1,
Olympia Roeva
1,2,
Peter Vassilev
1 and
Tania Pencheva
1,*
1
Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
2
Institute of Robotics, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
*
Author to whom correspondence should be addressed.
Processes 2023, 11(2), 427; https://doi.org/10.3390/pr11020427
Submission received: 9 December 2022 / Revised: 23 January 2023 / Accepted: 28 January 2023 / Published: 31 January 2023
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Abstract

In this paper, a new hybrid MpGA-CS is elaborated between multi-population genetic algorithm (MpGA) and cuckoo search (CS) metaheuristic. Developed MpGA-CS has been adapted and tested consequently for modelling of bacteria and yeast fermentation processes (FP), due to their great impact on different industrial areas. In parallel, classic MpGA, classic CS, and a new hybrid MpGA-CS have been separately applied for parameter identification of E. coli and S. cerevisiae FP models. For completeness, the newly elaborated MpGA-CS has been compared with two additional nature-inspired algorithms; namely, artificial bee colony algorithm (ABC) and water cycle algorithm (WCA). The comparison has been carried out based on numerical and statistical tests, such as ANOVA, Friedman, and Wilcoxon tests. The obtained results show that the hybrid metaheuristic MpGA-CS, presented herein for the first time, has been distinguished as the most reliable among the investigated algorithms to further save computational resources.
Keywords: multi-population genetic algorithm; cuckoo search; hybrid technique; parameter identification; fed-batch fermentation models; E. coli; S. cerevisiae multi-population genetic algorithm; cuckoo search; hybrid technique; parameter identification; fed-batch fermentation models; E. coli; S. cerevisiae

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MDPI and ACS Style

Angelova, M.; Roeva, O.; Vassilev, P.; Pencheva, T. Multi-Population Genetic Algorithm and Cuckoo Search Hybrid Technique for Parameter Identification of Fermentation Process Models. Processes 2023, 11, 427. https://doi.org/10.3390/pr11020427

AMA Style

Angelova M, Roeva O, Vassilev P, Pencheva T. Multi-Population Genetic Algorithm and Cuckoo Search Hybrid Technique for Parameter Identification of Fermentation Process Models. Processes. 2023; 11(2):427. https://doi.org/10.3390/pr11020427

Chicago/Turabian Style

Angelova, Maria, Olympia Roeva, Peter Vassilev, and Tania Pencheva. 2023. "Multi-Population Genetic Algorithm and Cuckoo Search Hybrid Technique for Parameter Identification of Fermentation Process Models" Processes 11, no. 2: 427. https://doi.org/10.3390/pr11020427

APA Style

Angelova, M., Roeva, O., Vassilev, P., & Pencheva, T. (2023). Multi-Population Genetic Algorithm and Cuckoo Search Hybrid Technique for Parameter Identification of Fermentation Process Models. Processes, 11(2), 427. https://doi.org/10.3390/pr11020427

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