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Quantum Bridge Analytics II: QUBO-Plus, network optimization and combinatorial chaining for asset exchange

Quantum Bridge Analytics relates to methods and systems for hybrid classical-quantum computing, and is devoted to developing tools for bridging classical and quantum computing to gain the benefits of their alliance in the present and enable enhanced practical application of quantum computing in the...

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Detalles Bibliográficos
Autores principales: Glover, Fred, Kochenberger, Gary, Ma, Moses, Du, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9059917/
https://www.ncbi.nlm.nih.gov/pubmed/35531564
http://dx.doi.org/10.1007/s10479-022-04695-3
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author Glover, Fred
Kochenberger, Gary
Ma, Moses
Du, Yu
author_facet Glover, Fred
Kochenberger, Gary
Ma, Moses
Du, Yu
author_sort Glover, Fred
collection PubMed
description Quantum Bridge Analytics relates to methods and systems for hybrid classical-quantum computing, and is devoted to developing tools for bridging classical and quantum computing to gain the benefits of their alliance in the present and enable enhanced practical application of quantum computing in the future. This is the second of a two-part tutorial that surveys key elements of Quantum Bridge Analytics and its applications. Part I focused on the Quadratic Unconstrained Binary Optimization (QUBO) model which is presently the most widely applied optimization model in the quantum computing area, and which unifies a rich variety of combinatorial optimization problems. Part II (the present paper) introduces the domain of QUBO-Plus models that enables a larger range of problems to be handled effectively. After illustrating the scope of these QUBO-Plus models with examples, we give special attention to an important instance of these models called the Asset Exchange Problem (AEP). Solutions to the AEP enable market players to identify exchanges of assets that benefit all participants. Such exchanges are generated by a combination of two optimization technologies for this class of QUBO-Plus models, one grounded in network optimization and one based on a new metaheuristic optimization approach called combinatorial chaining. This combination opens the door to expanding the links to quantum computing applications established by QUBO models through the Quantum Bridge Analytics perspective. We show how the modeling and solution capability for the AEP instance of QUBO-Plus models provides a framework for solving a broad range of problems arising in financial, industrial, scientific, and social settings.
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spelling pubmed-90599172022-05-03 Quantum Bridge Analytics II: QUBO-Plus, network optimization and combinatorial chaining for asset exchange Glover, Fred Kochenberger, Gary Ma, Moses Du, Yu Ann Oper Res Original Research Quantum Bridge Analytics relates to methods and systems for hybrid classical-quantum computing, and is devoted to developing tools for bridging classical and quantum computing to gain the benefits of their alliance in the present and enable enhanced practical application of quantum computing in the future. This is the second of a two-part tutorial that surveys key elements of Quantum Bridge Analytics and its applications. Part I focused on the Quadratic Unconstrained Binary Optimization (QUBO) model which is presently the most widely applied optimization model in the quantum computing area, and which unifies a rich variety of combinatorial optimization problems. Part II (the present paper) introduces the domain of QUBO-Plus models that enables a larger range of problems to be handled effectively. After illustrating the scope of these QUBO-Plus models with examples, we give special attention to an important instance of these models called the Asset Exchange Problem (AEP). Solutions to the AEP enable market players to identify exchanges of assets that benefit all participants. Such exchanges are generated by a combination of two optimization technologies for this class of QUBO-Plus models, one grounded in network optimization and one based on a new metaheuristic optimization approach called combinatorial chaining. This combination opens the door to expanding the links to quantum computing applications established by QUBO models through the Quantum Bridge Analytics perspective. We show how the modeling and solution capability for the AEP instance of QUBO-Plus models provides a framework for solving a broad range of problems arising in financial, industrial, scientific, and social settings. Springer US 2022-05-02 2022 /pmc/articles/PMC9059917/ /pubmed/35531564 http://dx.doi.org/10.1007/s10479-022-04695-3 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Research
Glover, Fred
Kochenberger, Gary
Ma, Moses
Du, Yu
Quantum Bridge Analytics II: QUBO-Plus, network optimization and combinatorial chaining for asset exchange
title Quantum Bridge Analytics II: QUBO-Plus, network optimization and combinatorial chaining for asset exchange
title_full Quantum Bridge Analytics II: QUBO-Plus, network optimization and combinatorial chaining for asset exchange
title_fullStr Quantum Bridge Analytics II: QUBO-Plus, network optimization and combinatorial chaining for asset exchange
title_full_unstemmed Quantum Bridge Analytics II: QUBO-Plus, network optimization and combinatorial chaining for asset exchange
title_short Quantum Bridge Analytics II: QUBO-Plus, network optimization and combinatorial chaining for asset exchange
title_sort quantum bridge analytics ii: qubo-plus, network optimization and combinatorial chaining for asset exchange
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9059917/
https://www.ncbi.nlm.nih.gov/pubmed/35531564
http://dx.doi.org/10.1007/s10479-022-04695-3
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