Constraint-aware initialization and hybrid XY-X mixer in QAOA for VRP yield lower average energies and higher feasible-solution ratios than standard QAOA across ideal, finite-shot, and noisy simulations.
Warm-starting QAOA with XY mixers: A novel approach for quantum- enhanced vehicle routing optimization
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A nested amplitude amplification protocol for knapsack performs partial amplification on initial variables via an Inner Iteration Finder before global GAS, reducing solution improvement costs versus baseline in simulations on large instances.
Generic QAOA's claimed exponential feasibility bottleneck on permutation-constrained problems is not proven; the main bound has a 2^N normalization error and is false as stated.
citing papers explorer
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Improving Feasibility in Quantum Approximate Optimization Algorithm for Vehicle Routing via Constraint-Aware Initialization and Hybrid XY-X Mixing
Constraint-aware initialization and hybrid XY-X mixer in QAOA for VRP yield lower average energies and higher feasible-solution ratios than standard QAOA across ideal, finite-shot, and noisy simulations.
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A Nested Amplitude Amplification Protocol for the Binary Knapsack Problem
A nested amplitude amplification protocol for knapsack performs partial amplification on initial variables via an Inner Iteration Finder before global GAS, reducing solution improvement costs versus baseline in simulations on large instances.
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Fundamental Limitations of QAOA on Constrained Problems and a Route to Exponential Enhancement
Generic QAOA's claimed exponential feasibility bottleneck on permutation-constrained problems is not proven; the main bound has a 2^N normalization error and is false as stated.