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The Minimum s-Club Cover problem (Min s-Club Cover) has important applications in social network analysis and group object modeling. The objective of Min s-Club Cover is to determine the fewest possible s-Clubs to cover a graph’s vertices. This study describes a hybrid between evolutionary multitask optimization and a local search algorithm that is inspired by a simulated annealing algorithm to address the Min s-Club Cover. In each generation, the local search algorithm optimizes the best individual for each task. We evaluate our algorithm using benchmark instances from the DIMACS library. Experimental results demonstrate that our approach outperforms existing methods.

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A Hybrid Multifactorial Evolutionary Algorithm for the Minimum s-Club Cover Problem

  • 会议论文

  • 发表日期：

    2025年

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  • Pham Dinh Thanh,
  • Do Tuan Anh

摘要

The Minimum s-Club Cover problem (Min s-Club Cover) has important applications in social network analysis and group object modeling. The objective of Min s-Club Cover is to determine the fewest possible s-Clubs to cover a graph’s vertices. This study describes a hybrid between evolutionary multitask optimization and a local search algorithm that is inspired by a simulated annealing algorithm to address the Min s-Club Cover. In each generation, the local search algorithm optimizes the best individual for each task. We evaluate our algorithm using benchmark instances from the DIMACS library. Experimental results demonstrate that our approach outperforms existing methods.