Quantum Knapsack Problem Benchmark

Benchmark of quantum optimization algorithms applied to the knapsack problem, a fundamental NP-hard constrained combinatorial optimization problem. Recent advances include copula-QAOA for hardware-efficient constraint handling and Amplitude Amplification-mixer QAOA (AAM-QAOA), which uses a quantum tree generator for feasible-solution state preparation. Benchmark sets test instances with up to 20 items.[1]

  • Algorithm: QAOA / Copula-QAOA / AAM-QAOA
  • Category: optimization
  • Qubits: 20
  • Framework: Qiskit, PennyLane
  • Reproducible: Yes
  • Published:
  • knapsack
  • constrained-optimization
  • QAOA
  • combinatorial
  • NISQ

What algorithm does Quantum Knapsack Problem Benchmark use?

Quantum Knapsack Problem Benchmark uses the QAOA / Copula-QAOA / AAM-QAOA algorithm, categorized under optimization.

Frequently Asked Questions

What is the Quantum Knapsack Problem Benchmark benchmark?

Benchmark of quantum optimization algorithms applied to the knapsack problem, a fundamental NP-hard constrained combinatorial optimization problem. Recent advances include copula-QAOA for hardware-efficient constraint handling and Amplitude Amplification-mixer QAOA (AAM-QAOA), which uses a quantum tree generator for feasible-solution state preparation. Benchmark sets test instances with up to 20 items.

Is Quantum Knapsack Problem Benchmark reproducible?

Yes, this benchmark is reproducible.

Sources

  1. "Quantum tree generator improves QAOA state-of-the-art for the knapsack problem", accessed 2026-03-19 — arXiv
  2. "A Comparative Study of Quantum Optimization Techniques for Solving Combinatorial Optimization Benchmark Problems", accessed 2026-03-19 — arXiv