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Influence of Ant Colony Optimization Parameters on the Algorithm Performance

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Large-Scale Scientific Computing (LSSC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10665))

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Abstract

In this paper an Ant Colony Optimization (ACO) algorithm for parameter identification of cultivation process models is proposed. In computational point of view it is a hard problem. To be solved problem with a high accuracy in reasonable time, metaheuristic techniques are used. The influence of ACO algorithm parameters, namely number of agents (ants) and number of iterations, to the quality of achieved solution is investigated. As a case study an E. coli fed-batch cultivation process is explored. Based on the parameter identification of E. coli MC4110 cultivation process model some conclusions for the optimal ACO parameter settings are done.

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Acknowledgments

Work presented here is partially supported by the Bulgarian National Scientific Fund under Grants DFNI I02/20 “Efficient Parallel Algorithms for Large Scale Computational Problems” and “New Instruments for Knowledge Discovery from Data, and their Modelling” DN 02/10.

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Authors and Affiliations

  1. Institute of Information and Communication Technologies – BAS, Acad. G. Bonchev Str., bl. 25A, 1113, Sofia, Bulgaria

    Stefka Fidanova

  2. Institute of Biophysics and Biomedical Engineering – BAS, Acad. G. Bonchev Str., bl. 105, 1113, Sofia, Bulgaria

    Olympia Roeva

Authors
  1. Stefka Fidanova
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  2. Olympia Roeva
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Correspondence to Stefka Fidanova .

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Editors and Affiliations

  1. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Ivan Lirkov

  2. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Svetozar Margenov

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Fidanova, S., Roeva, O. (2018). Influence of Ant Colony Optimization Parameters on the Algorithm Performance. In: Lirkov, I., Margenov, S. (eds) Large-Scale Scientific Computing. LSSC 2017. Lecture Notes in Computer Science(), vol 10665. Springer, Cham. https://doi.org/10.1007/978-3-319-73441-5_38

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  • DOI: https://doi.org/10.1007/978-3-319-73441-5_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73440-8

  • Online ISBN: 978-3-319-73441-5

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