TY - GEN
T1 - Focusing on the hybrid quantum computing - Tabu search algorithm
T2 - 2021 Genetic and Evolutionary Computation Conference, GECCO 2021
AU - Osaba, Eneko
AU - Villar-Rodriguez, Esther
AU - Oregi, Izaskun
AU - Moreno-Fernandez-De-Leceta, Aitor
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/7/7
Y1 - 2021/7/7
N2 - 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. Thus, current solving systems suffer 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. Furthermore, as an additional contribution, this work also supposes the first solving 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.
AB - 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. Thus, current solving systems suffer 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. Furthermore, as an additional contribution, this work also supposes the first solving 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.
KW - DWAVE
KW - metaheuristic optimization
KW - quantum computing
KW - transfer optimization
KW - traveling salesman problem
UR - http://www.scopus.com/inward/record.url?scp=85111025831&partnerID=8YFLogxK
U2 - 10.1145/3449726.3463123
DO - 10.1145/3449726.3463123
M3 - Conference contribution
AN - SCOPUS:85111025831
T3 - GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion
SP - 1476
EP - 1482
BT - GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion
PB - Association for Computing Machinery, Inc
Y2 - 10 July 2021 through 14 July 2021
ER -