## 4 Proposed Load Scheduling Model
### Artificial Hummingbird Optimization Algorithm
The data of the user energy consumption, pricing rate, and sampling time (15 min) are the same for both works. However, the work in [16] is considered with PV and batteries available for each user. Table 9 shows the comparison results for aggregated users' peak consumption and energy cost saving. The cost saving based on ToU for [16] is about 15.21% and about 14% for peak saving. Moreover, regarding the developed model and with the same pricing rate, the results are 40% and 64% for cost and peak saving, respectively. Moreover, with the proposed approach, PV and the battery have not been considered, which in turn has provided less cost for users utilizing the proposed model. For the proposed load scheduling, the cost and energy saving based on the ACLPS pricing rate are 81% and 68%, respectively. According to the presented results, the proposed model provides higher energy and cost saving, which benefits both utility companies and users. This is achieved by reducing the required energy consumption for the utility company and through minimizing the cost regarding the user. ## 7 Conclusions

Multi-user load scheduling is presented for combining MAHA-MEREC-VIKOR methods to achieve the optimal cost, peak, and user inconvenience simultaneously. The proposed method realizes both cost and peak energy saving for the first, second, third, fourth, and fifth users, which are (33% and 17%), (43% and 49%), (24% and 43%), (38% and 56%), and \begin{table}
\begin{tabular}{c c c} \hline \hline
**References** & **Cost Reduction (\%)** & **Peak Load Reduction (\%)** \\ \hline
[15] & 15.21 & 14 \\ Proposed method & 40 & 64 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Comparison results with [16]. Figure 7: Power consumption without and with scheduling for ToU and ACLPS for all users. (38% and 38%), respectively. With aggregated load consumption for all users (five users) based on ToU, the cost and peak savings are 40% and 64%, respectively. Regarding ACLPS, the cost and peak savings for the first, second, third, fourth, and fifth users are (94% and 55%), (94% and 49%), (93% and 43%), (95% and 56%), and (95% and 38%). Regarding all users and based on ACLPs, the cost and peak savings are 81% and 68%, respectively. Moreover, to highlight the significance of the proposed model, the results of the presented method are validated against other techniques published in recent contributions within the literature. According to the validation, the results of the proposed method provided superior cost and peak load saving. The importance of the proposed model was realized by saving the cost of energy for users and reducing the peak load for a utility company with an acceptable level of user inconvenience. Different pricing schemes were considered in this work to clearly present the effect of the price rate on the proposed method. Regarding future directions that are based on the proposed work, the allowance time period of ACLPS can be adaptive according to the user demand rather than constant value. Furthermore, the parameters of MAHA can be dynamically changed based on various objective functions. In addition, adding renewable energy sources to the user side provides more flexibility for demand management during peak periods. **Author Contributions:** Conceptualization, H.T.H. and D.H.M. ; methodology, H.T.H. and D.H.M. ; software, H.T.H. and D.H.M. ; validation, H.T.H. and D.H.M. ; formal analysis, H.T.H., D.H.M. and Y.A.-N.; investigation, H.T.H. and Y.A.-N.; resources, G.G.S. and D.H.M. ; data curation, H.T.H. ; writing--original draft preparation, H.T.H. and D.H.M. ; writing--review and editing, D.H.M. and Y.A.-N.; visualization, H.T.H. and G.G.S. ; supervision, H.T.H. and D.H.M. ; project administration, H.T.H. All authors have read and agreed to the published version of the manuscript. **Funding:** This research received no external funding. **Data Availability Statement:** Data are contained within the article.