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A scalable quantum-enhanced greedy algorithm for maximum independent set problems,

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Rolling Stock Planning Using the Quantum Approximate Optimization Algorithm

quant-ph · 2026-06-09 · unverdicted · novelty 4.0

The authors cast rolling stock planning as maximum-weight independent set on a cycle graph, then apply a divide-and-conquer hybrid that solves subgraphs with QAOA (simulated and on IQM Emerald) and show larger subgraphs yield better solutions than smaller ones or pure classical heuristics.

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  • Rolling Stock Planning Using the Quantum Approximate Optimization Algorithm quant-ph · 2026-06-09 · unverdicted · none · ref 8

    The authors cast rolling stock planning as maximum-weight independent set on a cycle graph, then apply a divide-and-conquer hybrid that solves subgraphs with QAOA (simulated and on IQM Emerald) and show larger subgraphs yield better solutions than smaller ones or pure classical heuristics.