Nurse Scheduling Problem via PyQUBO

TL;DR

This paper formulates the nurse scheduling problem as a QUBO and applies simulated annealing to optimize staffing, demonstrating promising results and potential for broader complex optimization applications.

Contribution

It introduces a QUBO-based formulation for nurse scheduling and applies quantum-inspired optimization techniques, advancing methods for healthcare staffing problems.

Findings

Effective QUBO formulation for nurse scheduling

Simulated annealing improves workload balance

Potential for extending to other complex optimization tasks

Abstract

The nurse scheduling problem is a critical optimization challenge in healthcare management. It aims to balance staffing demands, nurse satisfaction, and patient care quality. Corresponding to the constraints inherent in this scheduling problem, we detail the mathematical formulation step-by-step. We then utilize a quantum-inspired technique, the simulated annealing algorithm, and a quadratic unconstrained binary optimization model to optimize workload and increase nurse preferences. Numerical experiments are implemented to show the capacity of our proposed techniques. Our findings indicate a promising direction for future research, with potential applications extending beyond nurse scheduling to other complex optimization problems.