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arXiv · 2404.05448

Efficient Encodings of the Travelling Salesperson Problem for Variational Quantum Algorithms

Manuel Schnaus·Lilly Palackal·Benedikt Poggel·Xiomara Runge·Hans Ehm·Jeanette Miriam Lorenz·Christian B. Mendl
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Abstract

Routing problems are a common optimization problem in industrial applications, which occur on a large scale in supply chain planning. Due to classical limitations for solving NP-hard problems, quantum computing hopes to improve upon speed or solution quality. Several suggestions have been made for encodings of routing problems to solve them with variational quantum algorithms. However, for an end user it is hard to decide a priori which encoding will give the best solutions according to their needs. In this work, we investigate different encodings for the Travelling Salesperson Problem. We compare their scaling and performance when using the Quantum Approximate Optimization Algorithm and the Variational Quantum Eigensolver and provide a clear guide for users when to choose which encoding. For small instances, we find evidence that the permutation encoding can yield good results since it does not suffer from feasibility issues.

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Manuel Schnaus, Lilly Palackal, Benedikt Poggel, Xiomara Runge, Hans Ehm, Jeanette Miriam Lorenz, Christian B. Mendl. 2024-04-08. Efficient Encodings of the Travelling Salesperson Problem for Variational Quantum Algorithms. https://doi.org/10.1109/qsw62656.2024.00022

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