AI RESEARCH
Learning to Solve the Quadratic Assignment Problem with Warm-Started MCMC Finetuning
arXiv CS.LG
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ArXi:2604.20109v1 Announce Type: new The quadratic assignment problem (QAP) is a fundamental NP-hard task that poses significant challenges for both traditional heuristics and modern learning-based solvers. Existing QAP solvers still struggle to achieve consistently competitive performance across structurally diverse real-world instances. To bridge this performance gap, we propose PLMA, an innovative permutation learning framework.