Constraint-Preserving QAOA for Personnel Rostering: Coverage-Preserving and Guarded-XY Mixer Constructions

Quantum Physics arXiv:2607.09145 (quant-ph) [Submitted on 10 Jul 2026] Title:Constraint-Preserving QAOA for Personnel Rostering: Coverage-Preserving and Guarded-XY Mixer Constructions Authors:Aruna Gupta, S R Hassan View a PDF of the paper titled Constraint-Preserving QAOA for Personnel Rostering: Coverage-Preserving and Guarded-XY Mixer Constructions, by Aruna Gupta and S R Hassan View PDF HTML (experimental) Abstract:The Quantum Approximate Optimization Algorithm (QAOA) is a promising framework for combinatorial optimization, but constrained problems are commonly handled using energetic penalty terms that require calibration and allow infeasible configurations to remain dynamically accessible. We develop a constraint-preserving QAOA framework for personnel rostering in which hard scheduling constraints are embedded directly into the mixer Hamiltonian. Using a binary rostering model with daily coverage and no-consecutive-duty constraints, we formulate the dynamics from a transition-graph perspective and introduce a guarded-XY mixer that confines the evolution to the fully feasible scheduling manifold. We further distinguish feasibility preservation from feasible-transition design and propose a tight-pattern extension that introduces collective feasible exchanges in saturated workload segments where local guarded exchanges alone are insufficient. Exact statevector simulations demonstrate that, compared with Penalty-X and Coverage-XY formulations under both expectation-value and Conditional Value-at-Risk optimization, the proposed approach eliminates hard-constraint penalty calibration, guarantees feasible evolution by construction, and consistently yields higher-quality output distributions with stronger concentration on optimal feasible schedules. To the best of our knowledge, this is the first constraint-preserving QAOA formulation for personnel rostering, and the transition-graph framework is readily applicable to a broad class of constrained quantum optimization problems. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2607.09145 [quant-ph] (or arXiv:2607.09145v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2607.09145 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Aruna Gupta [view email] [v1] Fri, 10 Jul 2026 06:58:45 UTC (8,277 KB) Full-text links: Access Paper: View a PDF of the paper titled Constraint-Preserving QAOA for Personnel Rostering: Coverage-Preserving and Guarded-XY Mixer Constructions, by Aruna Gupta and S R HassanView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-07 References & Citations INSPIRE HEP NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)