InterCriteria Analysis of Genetic Algorithms Performance

  • Olympia Roeva
  • Peter Vassilev
  • Stefka Fidanova
  • Marcin Paprzycki
Part of the Studies in Computational Intelligence book series (SCI, volume 655)


In this paper we apply InterCriteria Analysis (ICrA) approach based on the apparatus of Index Matrices and Intuitionistic Fuzzy Sets. The main idea is to use ICrA to establish the existing relations and dependencies of defined parameters in a non-linear model of an E. coli fed-batch cultivation process. We perform a series of model identification procedures applying Genetic Algorithms (GAs). We proposed a schema of ICrA of ICrA results to examine the obtained model identification results. The discussion about existing relations and dependencies is performed according to criteria defined in terms of ICrA. We consider as ICrA criteria model parameters and GAs outcomes on the one hand, and 14 differently tuned GAs on the other. Based on the results, we observe the mutual relations between model parameters and GAs outcomes, such as computation time and objective function value. Moreover, some conclusions about the preferred tuned GAs for the considered model parameter identification in terms of achieved accuracy for given computation time are presented.


InterCriteria analysis Index matrices Intuitionistic fuzzy sets Genetic algorithm Parameter identification E. coli Cultivation process 



The work presented here is partially supported by the Bulgarian National Scientific Fund under Grant DFNI-I02/5 and by the Polish-Bulgarian collaborative Grant “Parallel and Distributed Computing Practices”.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Olympia Roeva
    • 1
  • Peter Vassilev
    • 1
  • Stefka Fidanova
    • 2
  • Marcin Paprzycki
    • 3
  1. 1.Institute of Biophysics and Biomedical EngineeringBulgarian Academy of SciencesSofiaBulgaria
  2. 2.Institute of Information and Communication TechnologyBulgarian Academy of SciencesSofiaBulgaria
  3. 3.System Research Institute Polish Academy of SciencesWarsaw and Management AcademyWarsawPoland

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