# Optimization of an appointment scheduling problem for healthcare systems based on the quality of fairness service using whale optimization algorithm and NSGA-II

## TL;DR

This paper proposes using the whale optimization algorithm and NSGA-II to improve fairness in hospital appointment scheduling, aiming to enhance patient satisfaction.

## Contribution

The novel contribution is applying WOA and NSGA-II with a Pareto archive to optimize fairness in healthcare appointment scheduling.

## Key findings

- The WOA and NSGA-II approaches outperformed traditional scheduling strategies in fairness and patient satisfaction.
- The FCFS policy was found to be a key priority factor in optimizing appointment scheduling.
- Simulation results showed improved performance using the proposed multi-criteria optimization methods.

## Abstract

Effective appointment scheduling (EAS) is essential for the quality and patient satisfaction in hospital management. Healthcare schedulers typically refer patients to a suitable period of service before the admission call closes. The appointment date can no longer be adjusted. This research presents the whale optimization algorithm (WOA) based on the Pareto archive and NSGA-II algorithm to solve the appointment scheduling model by considering the simulation approach. Based on these two algorithms, this paper has addressed the multi-criteria method in appointment scheduling. This paper computes WOA and NSGA with various hypotheses to meet the analysis and different factors related to patients in the hospital. In the last part of the model, this paper has analyzed NSGA and WOA with three cases. Fairness policy first come first serve (FCFS) considers the most priority factor to obtain from figure to strategies optimized solution for best satisfaction results. In the proposed NSGA, the FCFS approach and the WOA approach are contrasted. Numerical results indicate that both the FCFS and WOA approaches outperform the strategy optimized by the proposed algorithm.