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Variable Neighborhood Search Approach to Community Detection Problem

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Numerical Methods and Applications (NMA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13858))

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Abstract

Community detection on graphs can help people gain insight into the network’s structural organization, and grasp the relationships between network nodes for various types of networks, such as transportation networks, biological networks, electric power networks, social networks, blockchain, etc. The community in the network refers to the subset of nodes that have greater similarity, i.e. have relatively close internal connections. They should also have obvious differences with members from different communities, i.e. relatively sparse external connections. Solving the community detection problem is one of long standing and challenging optimization tasks usually treated by metaheuristic methods. Thus, we address it by basic variable neighborhood search (BVNS) approach using modularity as the score for measuring quality of solutions. The conducted experimental evaluation on well-known benchmark examples revealed the best combination of BVNS parameters. Preliminary results of applying BVNS with thus obtained parameters are competitive in comparison to the state-of-the-art methods from the literature.

This work has been funded by the Serbian Ministry of Education, Science and Technological Development, Agreement No. 451-03-9/2021-14/200029 and by the Science Fund of Republic of Serbia, under the project “Advanced Artificial Intelligence Techniques for Analysis and Design of System Components Based on Trustworthy BlockChain Technology (AI4TrustBC)”.

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Authors and Affiliations

  1. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia

    Djordje Jovanović, Tatjana Davidović, Dragan Urošević & Tatjana Jakšić Krüger

  2. School of Professional Graduate Studies at Great Valley, The Pennsylvania State University, Malvern, PA, USA

    Dušan Ramljak

Authors
  1. Djordje Jovanović
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  2. Tatjana Davidović
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  3. Dragan Urošević
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  4. Tatjana Jakšić Krüger
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  5. Dušan Ramljak
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Corresponding author

Correspondence to Djordje Jovanović .

Editor information

Editors and Affiliations

  1. Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Ivan Georgiev

  2. Institute of Mechanics, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Maria Datcheva

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

    Krassimir Georgiev

  4. Sofia University “St. Kliment Ohridski”, Sofia, Bulgaria

    Geno Nikolov

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Jovanović, D., Davidović, T., Urošević, D., Krüger, T.J., Ramljak, D. (2023). Variable Neighborhood Search Approach to Community Detection Problem. In: Georgiev, I., Datcheva, M., Georgiev, K., Nikolov, G. (eds) Numerical Methods and Applications. NMA 2022. Lecture Notes in Computer Science, vol 13858. Springer, Cham. https://doi.org/10.1007/978-3-031-32412-3_17

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  • DOI: https://doi.org/10.1007/978-3-031-32412-3_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-32411-6

  • Online ISBN: 978-3-031-32412-3

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