Penalty weights in QUBO formulations: permutation problems

DOI10.1007/978-3-031-04148-8_11zbMath1499.90177arXiv2206.11040OpenAlexW4226343246MaRDI QIDQ2163796

Mayowa Ayodele

Publication date: 11 August 2022

Full work available at URL: https://arxiv.org/abs/2206.11040

zbMATH Keywords

permutationIsing modelconstraint handlingbinary quadratic problemdigital annealerpenalty weightsquadratic unconstrained binary optimisationquantum-inspired optimisation

Mathematics Subject Classification ID

Combinatorial optimization (90C27) Quantum computation (81P68)

Uses Software

• QAPLIB
• TSPLIB
• PyQUBO

Cites Work

• A Max-flow approach to improved lower bounds for quadratic unconstrained binary optimization (QUBO)
• QAPLIB - a quadratic assignment problem library
• Penalty and partitioning techniques to improve performance of QUBO solvers
• TSPLIB—A Traveling Salesman Problem Library
• PyQUBO: Python Library for Mapping Combinatorial Optimization Problems to QUBO Form
• Quantum bridge analytics. I: A tutorial on formulating and using QUBO models

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