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arXiv AI By Xiang Li, Shanshan Wang, Chenglong Xiao

Instance-Aware Algorithm Selection for Maximum Clique via a Dual-Channel Graph Neural Architecture

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The paper presents a dual‑channel graph neural architecture for selecting the best exact solver for the Maximum Clique Problem (MCP). It combines a Graph Attention Network that captures local neighborhood patterns with a Multilayer Perceptron that models global statistical descriptors, trained on a benchmark of four state‑of‑the‑art solvers evaluated across diverse graph instances. The resulting model achieves 90.43 % test accuracy, outperforming classical baselines and the single‑best solver.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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