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Solving the Multitasking Robust Influence Maximization Problem on Networks using a Multi-factorial Evolutionary Algorithm

Published: 24 July 2023 Publication History

Abstract

Recently, influence maximization has become a key research area in complex networks, focusing on selecting optimal seed sets for propagation in the network. However, networks often face complex environments with node/link failures or external attacks, making robustness critical for seed nodes. This robust influence maximization problem is not comprehensively addressed by existing approaches, which fail to combine information or knowledge across multiple scenarios. To address this, this paper introduces multi-task optimization theory, designing an evolutionary algorithm, MFEANet, to consider diversity gene information and multiple optimization scenarios simultaneously. MFEANet achieves competitive performance in experimental results compared to existing methods.

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Cited By

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  • (2025)Distributed Robust Multitask Clustering in Wireless Sensor Networks using Multi-Factorial Evolutionary AlgorithmJournal of Parallel and Distributed Computing10.1016/j.jpdc.2025.105038(105038)Online publication date: Jan-2025

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  1. Solving the Multitasking Robust Influence Maximization Problem on Networks using a Multi-factorial Evolutionary Algorithm

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    cover image ACM Conferences
    GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation
    July 2023
    2519 pages
    ISBN:9798400701207
    DOI:10.1145/3583133
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

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    Published: 24 July 2023

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    Author Tags

    1. complex networks
    2. influence maximization problem
    3. robustness
    4. evolutionary algorithm
    5. multi-tasking optimization

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    View all
    • (2025)Distributed Robust Multitask Clustering in Wireless Sensor Networks using Multi-Factorial Evolutionary AlgorithmJournal of Parallel and Distributed Computing10.1016/j.jpdc.2025.105038(105038)Online publication date: Jan-2025

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