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Investigation of Genetic Algorithm Performance Based on Different Algorithms for InterCriteria Relations Calculation

  • Tania Pencheva
  • Olympia Roeva
  • Maria Angelova
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10665)

Abstract

InterCriteria Analysis is a recently developed approach for the evaluation of the correlation between multiple objects against multiple criteria. As such, it is expected to prove any existing correlations between the criteria themselves or even to discover any new. In this investigation different algorithms for InterCriteria relations calculation are explored to render the influence of the genetic algorithm (GA) parameters on the algorithm performance. GA is chosen as an optimization technique as they are among the most widely used out of the biologically inspired approaches for global search. GA is here applied to parameter identification of a S. cerevisiae fed-batch fermentation process model.

Keywords

Genetic algorithm InterCriteria Analysis Parameter identification Fermentation process S. cerevisiae 

Notes

Acknowledgements

This work is partially supported by the National Science Fund of Bulgaria under the Grants DFNI-I-02-5 “InterCriteria Analysis – A New Approach to Decision Making” and DM-07/1 “Development of New Modified and Hybrid Metaheuristic Algorithms”.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Institute of Biophysics and Biomedical EngineeringBulgarian Academy of SciencesSofiaBulgaria

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