Quantum Optimization for Nurse Scheduling Problem (NSP)

This project explores the application of Quantum Optimization for solving scheduling problems. The code is designed to run on a D-Wave's QPU. Check out the project report.

Dependencies

To run this project, you'll need the following dependencies:

• Python (>=3.6)
• dimod API
• dwave-system

Usage

After you have installed all dependencies you can either download the .zip file manualy from GitHub or clone the repo with this command:

git clone https://github.com/ThomasLagkalis/QuantumOptimization-Scheduling.git

Now run the nurse_scheduling_problem.py. You must specify two parameters: the first parameter is the number of nurses and the second is the number of days for the schedule i.g. 2 nurses and 3 days. (note in your case it might be python instead of python3).

python3 nurse_scheduling_porblem.py 2 3

The default solver used is the classical one which uses brute force algorithm to minimize the objective functio. If you want to use the hybrid (quantum-classical) solver you can specify it with the option: --hybrid

python3 nurse_scheduling_porblem.py 2 3 --hybrid

Results

After you run the programm the results should look something like this: