Standard QAOA faces an intrinsic feasibility bottleneck on permutation problems that CE QAOA overcomes with an exponential gain in feasible probability for sublinear-to-linear depths under mild hypergraph growth.
Warm-starting QAOA with XY mixers: A novel approach for quantum- enhanced vehicle routing optimization,
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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.
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.
citing papers explorer
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Fundamental Limitations of QAOA on Constrained Problems and a Route to Exponential Enhancement
Standard QAOA faces an intrinsic feasibility bottleneck on permutation problems that CE QAOA overcomes with an exponential gain in feasible probability for sublinear-to-linear depths under mild hypergraph growth.
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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.