Optimizing Human Resource Allocation in Long-Term Care Using Quantum and Digital Annealing

This study proposes a Quadratic Unconstrained Binary Optimization (QUBO) optimization model for scheduling home care workers in long-term care services. The Simulated Annealing (SA) algorithm, D-Wave Hybrid quantum annealer, Compal Quantix digital annealer, and Fujitsu DA3 digital annealer are conducted for performance evaluations on the proposed model. Experimental results show that the Compal Quantix and Fujitsu DA3 digital annealers significantly reduce the commuting distance of home care workers for optimizing human resource allocation more effectively than other schemes.