Using an \(A^\ast\)-based framework for decomposing combinatorial optimization problems to employ NISQ computers

DOI10.1007/s11128-023-04115-wOpenAlexW4387091521MaRDI QIDQ6048724

Simon Garhofer, Oliver Bringmann

Publication date: 13 October 2023

Published in: Quantum Information Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11128-023-04115-w

zbMATH Keywords

combinatorial optimizationapproximationproblem decompositiontraveling salesperson problem

Mathematics Subject Classification ID

Quantum computation (81P68)

Cites Work

• A distribution-free TSP tour length estimation model for random graphs
• Reducing the size of combinatorial optimization problems using the operator vaccine by fuzzy selector with adaptive heuristics
• Estimating the length of the optimal TSP tour: An empirical study using regression and neural networks
• From the quantum approximate optimization algorithm to a quantum alternating operator ansatz
• A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem
• A Dynamic Programming Approach to Sequencing Problems
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