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All reviewers' comments have been addressed. The paper can be accepted.
[# PeerJ Staff Note - this decision was reviewed and approved by Daniel S. Katz, a PeerJ Computer Science Section Editor covering this Section #]
The revised manuscript has been properly improved.
The revised manuscript has been properly improved.
The revised manuscript has been properly improved.
no comment
no comment
no comment
The authors supplemented the work in an adequate way and acted according to all suggestions
The paper must be significantly improved. Please follow the reviewers' suggestions.
[# PeerJ Staff Note: Please ensure that all review comments are addressed in a rebuttal letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate. It is a common mistake to address reviewer questions in the rebuttal letter but not in the revised manuscript. If a reviewer raised a question then your readers will probably have the same question so you should ensure that the manuscript can stand alone without the rebuttal letter. Directions on how to prepare a rebuttal letter can be found at: https://peerj.com/benefits/academic-rebuttal-letters/ #]
The authors propose a new version of the Rao nonparametric algorithm and named it the Fully Informed Search Algorithm (FISA). The article includes an appropriate introduction and background to demonstrate how the work fits into the broader field of knowledge. However, I suggest the authors check the recent literature sources, from the previous two, or three years, to make the article up-to-date.
The structure of the article is in accordance with a standard format: Introduction, Related work, Methods, Results, and Conclusions. Figures are relevant to the content of the article, appropriately described and labeled. The paper includes all results relevant to the hypothesis.
The research question is well-defined, relevant and meaningful. It is explained how the research fills an identified knowledge gap.
The research is conducted in conformity with the prevailing ethical standards in the field. Methods are described with sufficient detail.
The obtained results are of interest to the general and academic audience. The conclusions are appropriately stated and connected to the original investigated question.
I suggest the following improvements:
1. It should be further discussed about future directions of research.
2. What are the limitations of this study?
3. It should be further discussed about the managerial implications of the research.
I propose to indicate more clearly in the title the broader application of the model - real-world optimization problems or more specifically - optimizing real-parameter shifted functions.
The summary and conclusion correspond to the essence of the work.
The use of terminology is correct and it complies with applicable standards.
The authors clearly explained the methodology and structure of the work. The authors clearly presented a well-known optimization problem, and ways and methods of solving it. The authors presented the limitations of metaheuristic models in solving optimization problems and indicated the need to develop new ones with special reference to the RAO algorithms.
In line, 177 authors said, „These functions have been successfully utilized in many articles“. I suggest the authors add appropriate references.
In the paper, the results for selected engineering problems are presented in a good way, tabularly, and clearly. I recommend that that part be supplemented with a short comment, or analysis, of the obtained results: line 251(Table 3, Table 4), line 280 (Table 5, Table 6), and line 321 (Table 7, Table 8).
The effectiveness of the proposed algorithm was assessed in comparison with three original Rao algorithms for test functions presented in CEC 317 2005 and CEC 2014 and engineering design optimization problems.
By comparing the results of the new model with the existing models, the justification of the application can be seen, and the authors plan further application of the model in other optimization problems in future research.
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