Year: 2026
Type: article
Abstract: In contemporary Japan, isolated parenting has become a serious social issue, increasing psychological stress on parents and potentially affecting children's development. Existing childcare support services tend to focus on physical assistance, while psychological support and community connections remain insufficient. To address this gap, we developed a service that connects parents with senior community members who have parenting experience, aiming to provide psychological support and foster intergenerational exchange. Achieving high-quality matching requires considering pair compatibility, balancing supporter workload, and handling scheduling constraints, which can be formulated as a combinatorial optimization problem. We represented this matching problem as a Quadratic Unconstrained Binary Optimization (QUBO) model and evaluated a quantum-annealing-based sampling pipeline against simulated annealing (SA) and the exact mixed-integer optimization solver Gurobi. In randomized benchmark instances, the QA-based pipeline generated high-quality and diverse matching candidates, particularly for larger instances; at [Formula: see text], the mean best relative error was 1.94% for QA with post-processing and 7.45% for SA. Furthermore, a proof-of-concept field experiment conducted in Sendai City, Japan, demonstrated that the framework can generate multiple high-quality matching candidates, enabling flexible scheduling in real-world operations.
Source: Scientific Reports
Authors: Yuuma Matsumoto, Taisei Takabayashi, Rima Sato, Rumiko Honda, Masayuki Ohzeki
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,690
Award: G3367521855
OpenAlex ID: W4415613347