An Ant Colony Optimisation Approach to the Densest k-Subgraph Problem*

Zoltán Tasnádi, Noémi Gaskó
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Abstract

The densest k-subgraph problem is a relaxation of the well-known maximum clique problem and consists of finding a subgraph with exactly k nodes and a maximum number of edges. An ant colony optimisation-based approach is proposed to solve this combinatorial optimisation problem. Numerical experiments show the effectiveness and potential of the proposed approach.
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最密集k子图问题的蚁群优化方法*
最密集k子图问题是众所周知的最大团问题的一个松弛,它包括找到一个恰好有k个节点和最大边数的子图。提出了一种基于蚁群优化的组合优化方法。数值实验证明了该方法的有效性和潜力。
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FERPModels: A Certification Framework for Expansion-Based QBF Solving Reducing Adversarial Vulnerability Using GANs Fully-adaptive Model for Broadcasting with Universal Lists An Ant Colony Optimisation Approach to the Densest k-Subgraph Problem* IPO-MAXSAT: The In-Parameter-Order Strategy combined with MaxSAT solving for Covering Array Generation
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