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Reverse quantum annealing approach to portfolio optimization problems
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“When it comes to more advanced quantum annealing methods, forward as well as reverse annealing have been applied to the nurse scheduling problem [69] and portfolio optimization [140].”
From Quantum Combinatorial Optimization in the NISQ Era: A Systematic Mapping Study (2024) · cites this paper as [140]
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Metadata
- Authors
- Venturelli, D., & Kondratyev, A.
- Affiliations
- Research Institute for Advanced Computer Science (US)
- Corresponding author
- Venturelli, Davide
- ORCID
- Venturelli, Davide
- Venue
- Quantum Machine Intelligence
- Published
- 2019-04-26
- Volume
- 1
- Issue
- 1-2
- Pages
- 17-30
- ISSN
- 2524-4906 (ISSN-L)
- 2524-4914
- OpenAlex
- W2897628955
- Cited by
- 233
- References
- 44
- Citations by year
- 2026: 21 · 2025: 44 · 2024: 38 · 2023: 32 · 2022: 29 · 2021: 34 · 2020: 23 · 2019: 11
- FWCI
- 11.42
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Quantum Machine Intelligence (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Science Foundation (164883)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Social Sciences › Decision Sciences › Management Science and Operations Research › Risk and Portfolio Optimization
- Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
- Keywords
- portfolio optimization, mean-variance portfolio, D-Wave quantum annealer, hybrid quantum-classical algorithms, greedy local search, solution time
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