A Quantum-Inspired Approach to Emergency Patient Allocation Using Digital Annealing
Abstract
This paper presents a quantum-inspired optimization scheme for patient allocation, aimed at the expedient and efficient distribution of medical resources. The objective is to minimize patients' waiting times and optimize the usage of available medical capacity by allocating patients to the most appropriate hospitals based on the severity of their injuries. This allocation problem is situated within the urban context, seeking to minimize the distance between patients and hospitals. Traditionally, solving such large-scale allocation problems in expansive urban areas poses significant computational challenges. However, by incorporating quantum-inspired methods, we model this problem as a Quadratic Unconstrained Binary Optimization (QUBO) model, which is solved using a digital annealer. We conducted an experimental study on the digital annealing device and compared its performance with that of a conventional simulated annealing algorithm. The results demonstrate that our proposed digital annealing approach to patient allocation offers superior performance and effectiveness.
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