Table 11.

The comparison between the models.

Authors	Model	Solution	Optimal function	Results
Rashid et al. (2020)	Hybridized WOAGWO with Solution Approach	Solving critical probability in pressure vessel design in hospital	Statistical test compute for unimodal and multimodal functions	Shows that WOAGWO outperforms other algorithms depending on the test
Oliva et al. (2020)	Mixed integer linear programming (MILP), two binary variants of WOA	Minimized cost feature and total waiting time	A particle swarm optimizer and a mixed statistical test called	Achieved the smallest number of selected features with the best classification accuracy in a minimum time
Tahir et al. (2020)	Implementing two stages, binary chaotic (BCGA) and WOA	Two stages fitness function and BCGA feature given significant classification accuracy	Evolutionary computing-based optimized patient’s waiting time	BCGA map perform better and find a robust subset as compared to other maps in enhancing the performance of raw WOA
The presented method	Inter Linear Programming and WOA technique	Resolves appointment scheduling and waiting time problems for effective FCFS policy and obtained patients satisfaction	Numerical results indicate that both the FCFS and WOA approaches are strategy optimized	Both the FCFS and the WOA strategies data to gain the most propriety (Fairness) results and patient satisfaction