Focusing on the Hybrid Quantum Computing -- Tabu Search Algorithm: new results on the Asymmetric Salesman Problem

• URL: http://arxiv.org/abs/2102.05919v1
• Date: Thu, 11 Feb 2021 10:08:44 GMT
• Title: Focusing on the Hybrid Quantum Computing -- Tabu Search Algorithm: new results on the Asymmetric Salesman Problem
• Authors: Eneko Osaba, Esther Villar-Rodriguez, Izaskun Oregi and Aitor Moreno-Fernandez-de-Leceta
• Abstract summary: This paper extends the results and findings of the recently proposed hybrid Quantum Computing - Tabu Search Algorithm for partitioning problems. As an additional contribution, this work supposes the first solver of the Asymmetric Traveling Salesman Problem using a Quantum Computing based method.
• Score: 1.672938048065882
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum Computing is an emerging paradigm which is gathering a lot of popularity in the current scientific and technological community. Widely conceived as the next frontier of computation, Quantum Computing is still at the dawn of its development being current solving systems suffering from significant limitations in terms of performance and capabilities. Some interesting approaches have been devised by researchers and practitioners in order to overcome these barriers, being quantum-classical hybrid algorithms one of the most often used solving schemes. The main goal of this paper is to extend the results and findings of the recently proposed hybrid Quantum Computing - Tabu Search Algorithm for partitioning problems. To do that, we focus our research on the adaptation of this method to the Asymmetric Traveling Salesman Problem. In overall, we have employed six well-known instances belonging to TSPLIB to assess the performance of Quantum Computing - Tabu Search Algorithm in comparison to QBSolv -- a state-of-the-art decomposing solver. Furthermore, as an additional contribution, this work also supposes the first solver of the Asymmetric Traveling Salesman Problem using a Quantum Computing based method. Aiming to boost whole community's research in QC, we have released the project's repository as open source code for further application and improvements.

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