Quantum Computing Approaches for Mission Covering Optimization

• URL: http://arxiv.org/abs/2205.02212v1
• Date: Wed, 4 May 2022 17:46:54 GMT
• Title: Quantum Computing Approaches for Mission Covering Optimization
• Authors: Massimiliano Cutugno, Annarita Giani, Paul M. Alsing, Laura Wessing, and Austars Schnore
• Abstract summary: We compare formulations of constrained optimization problems using Quantum Annealing techniques and the Quantum Alternating Operator Ansatz. We provide results from two different MCO scenarios and analyze results.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: 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.

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