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Towards Real Time Multi-robot Routing using Quantum Computing Technologies

Published: 14 January 2019 Publication History

Abstract

In this paper, we investigate the potential for current quantum computing technologies to provide good solutions to the NP-hard problem of routing multiple robots on a grid in real time. A hybrid quantum-classical approach has been presented in detail. Classical computation is used to generate candidate paths, while quantum annealing is used to select the optimal combination of paths. This second process is generally the most time consuming when performed clasically. The performance is benchmarked classically and on a D-Wave 2000Q with up to 200 robots and has shown that producing valid solutions for the problem of multi-robot routing is achievable with the current quantum annealing technology. The current limitations of using quantum annealing are also discussed.

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Cited By

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  • (2024)Quantum computer-aided job scheduling for storage and retrieval systemsat - Automatisierungstechnik10.1515/auto-2023-007272:1(15-21)Online publication date: 10-Jan-2024
  • (2024)A Systematic Mapping Study on Quantum and Quantum-inspired Algorithms in Operations ResearchACM Computing Surveys10.1145/370087457:3(1-35)Online publication date: 11-Nov-2024
  • (2024)New approach to solve unconstrained binary quadratic problemRAIRO - Operations Research10.1051/ro/202408758:4(3241-3262)Online publication date: 8-Aug-2024
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Information

Published In

cover image ACM Other conferences
HPCAsia '19: Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region
January 2019
143 pages
ISBN:9781450366328
DOI:10.1145/3293320
This work is licensed under a Creative Commons Attribution International 4.0 License.

In-Cooperation

  • Sun Yat-Sen University
  • CCF: China Computer Federation

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 January 2019

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HPC Asia 2019

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HPCAsia '19 Paper Acceptance Rate 15 of 32 submissions, 47%;
Overall Acceptance Rate 69 of 143 submissions, 48%

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Cited By

View all
  • (2024)Quantum computer-aided job scheduling for storage and retrieval systemsat - Automatisierungstechnik10.1515/auto-2023-007272:1(15-21)Online publication date: 10-Jan-2024
  • (2024)A Systematic Mapping Study on Quantum and Quantum-inspired Algorithms in Operations ResearchACM Computing Surveys10.1145/370087457:3(1-35)Online publication date: 11-Nov-2024
  • (2024)New approach to solve unconstrained binary quadratic problemRAIRO - Operations Research10.1051/ro/202408758:4(3241-3262)Online publication date: 8-Aug-2024
  • (2024)Comparing Adiabatic Quantum Computers for satellite images feature extractionFuture Generation Computer Systems10.1016/j.future.2024.04.027Online publication date: Apr-2024
  • (2024)Quantum robotics: a review of emerging trendsQuantum Machine Intelligence10.1007/s42484-024-00225-56:2Online publication date: 28-Nov-2024
  • (2024)Evaluating the practicality of quantum optimization algorithms for prototypical industrial applicationsQuantum Information Processing10.1007/s11128-024-04560-123:10Online publication date: 9-Oct-2024
  • (2023)Milestones on the Quantum Utility Highway: Quantum Annealing Case StudyACM Transactions on Quantum Computing10.1145/36253075:1(1-30)Online publication date: 16-Dec-2023
  • (2023)QOPTLib: A Quantum Computing Oriented Benchmark for Combinatorial Optimization ProblemsBenchmarks and Hybrid Algorithms in Optimization and Applications10.1007/978-981-99-3970-1_4(49-63)Online publication date: 22-Aug-2023
  • (2022)Quantum Computing in Supply Chain Management State of the Art and Research DirectionsAsian Journal of Logistics Management10.14710/ajlm.2022.143251:1(57-73)Online publication date: 23-May-2022
  • (2022)A Systematic Literature Review of Quantum Computing for Routing ProblemsIEEE Access10.1109/ACCESS.2022.317779010(55805-55817)Online publication date: 2022
  • Show More Cited By

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