论文标题
任务覆盖优化的量子计算方法
Quantum Computing Approaches for Mission Covering Optimization
论文作者
论文摘要
我们研究量子计算算法，以解决我们作为任务涵盖优化（MCO）的某些约束资源分配问题（MCO）。 We compare formulations of constrained optimization problems using Quantum Annealing techniques and the Quantum Alternating Operator Ansatz (Hadfield et al. arXiv:1709.03489v2, a generalized algorithm of the Quantum Approximate Optimization Algorithm, Farhi et al. arXiv:1411.4028v1) on D-Wave and IBM machines respectively using the following metrics: cost,时机，限制和使用的量子位。我们提供了两种不同的MCO场景的结果并分析结果。
We study quantum computing algorithms for solving certain constrained resource allocation problems we coin as Mission Covering Optimization (MCO). We compare formulations of constrained optimization problems using Quantum Annealing techniques and the Quantum Alternating Operator Ansatz (Hadfield et al. arXiv:1709.03489v2, a generalized algorithm of the Quantum Approximate Optimization Algorithm, Farhi et al. arXiv:1411.4028v1) on D-Wave and IBM machines respectively using the following metrics: cost, timing, constraints held, and qubits used. We provide results from two different MCO scenarios and analyze results.
