Next Article in Journal
Deep Learning in Financial Modeling: Predicting European Put Option Prices with Neural Networks
Previous Article in Journal
Total Outer-Independent Domination Number: Bounds and Algorithms
 
 
Article
Peer-Review Record

Hybrid Optimization Algorithm for Solving Attack-Response Optimization and Engineering Design Problems

Algorithms 2025, 18(3), 160; https://doi.org/10.3390/a18030160
by Ahmad K. Al Hwaitat 1,*, Hussam N. Fakhouri 2, Jamal Zraqou 3 and Najem Sirhan 3
Reviewer 1:
Reviewer 2: Anonymous
Algorithms 2025, 18(3), 160; https://doi.org/10.3390/a18030160
Submission received: 24 January 2025 / Revised: 8 February 2025 / Accepted: 5 March 2025 / Published: 10 March 2025
(This article belongs to the Section Algorithms for Multidisciplinary Applications)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The authors propose a new optimisation algorithm, DOJADE, combining the original JADE and DO. I found several points to improve the text:

- row 217 as I know, it is not true that both x1/x2 are selected from the union of P and A. Only x2 should be selected from P U A.

- there are typos, wrongly used articles, etc. The text needs a substantial linguistic/English care 

- there are missing references in the text ('??')

- it is not defined WHEN (IF) the DO processes occur in the modified DOJADE. It is specified HOW the processes work (in the original DO), but the reader has no idea if the processes are performed in each generation or after some condition...

- It is not fair that the enhanced variant of successful JADE is compared with rather simple(naive) nature-inspired methods. I also recommended using also original JADE or some more modern DE variant.

- The F8 plot in Fig. 5 has an interrupted convergence curve - why?

Comments on the Quality of English Language

I am not a Native speaker but the English needs some care.

Author Response

Response to Reviewer Comments

Dear Reviewer,

We sincerely appreciate your valuable feedback and constructive comments. We have carefully addressed all the points raised and revised our manuscript accordingly. Below, we provide a detailed response to each of your comments:

  1. Selection of x1 and x2 (Row 217)
    Thank you for pointing this out. We have corrected the explanation regarding the selection of x1x_1 and x2x_2, ensuring that only x2x_2 is selected from P∪AP \cup A while x1x_1 remains selected from PP.

  2. Linguistic and Grammatical Issues
    We have thoroughly revised the manuscript for linguistic accuracy and clarity. A professional language check has been conducted to improve readability and correct typos, grammatical errors, and inappropriate article usage.

  3. Missing References (‘??’ placeholders)
    All missing references have been properly inserted and verified to ensure completeness and correctness.

  4. Clarification of DO Processes in DOJADE
    We have explicitly defined when and under what conditions the DO processes occur in DOJADE. The revised text clarifies that the DO mechanism is applied in each generation to refine the population, ensuring a clear understanding of its integration into DOJADE.

  5. Benchmarking Against Competitive DE Variants
    We have compared with Multi-trial vector-based differential evolution (MTDE) optimizer which is DE vaarient that has been proposed in 2020.

  6. Interrupted Convergence Curve in Fig. 5 (F8 Plot)
    The interrupted convergence curve in Fig. 5 (F8 plot) was due to an issue in the visualization process. We have regenerated the figure to ensure a continuous and accurate representation of the convergence behavior.

We appreciate your time and effort in reviewing our work. Your comments have significantly contributed to improving the quality and clarity of our manuscript.

Best regards,

Dr. Ahmad 

Reviewer 2 Report

Comments and Suggestions for Authors

Authors in the paper proposed a hybrid algorithm named DOJADE, which combines the Dandelion Optimizer (DO) with the JADE algorithm (Adaptive Differential Evolution). The hybridization of these two algorithms is very interesting that authors proposed.

- What are the limitations of the DO and JADE algorithms that you aim to improve in this work?

- The equations 15 and 16 need more definition in the manuscript. How the adaptations with equations 25 and 26 have been done. These contexts need more explanation.

- In section 3.3, the computational complexity analysis has been described. It is necessary to compare with DO and JADE algorithms. Is there any improvement or the same or worse?

- The proposed algorithm should be explained with pseudocode and a flowchart.

 - It is necessary to show the compared algorithms boxplot analysis in Figure 6, the same as in Figure 10.

- Provide a brief overview of the method's limitations and practical benefits, also future work in the conclusion section.

- Several minor issues have been identified. It is necessary for the authors to review the entire paper to correct these errors.

 

Author Response

Dear Reviewer,

We greatly appreciate your time and effort in reviewing our manuscript. Your comments and suggestions have helped us improve the quality and clarity of our work. Below are our point-by-point responses detailing how we have addressed each of your concerns:

Limitations of DO and JADE:
We have now revised the Introduction and Related Work sections to clearly highlight the individual limitations of both Dandelion Optimizer (DO) and JADE algorithms (e.g., potential premature convergence in DO, and sensitivity to parameter settings in JADE). We describe how our proposed hybrid approach aims to mitigate these specific issues by combining the strengths of both methods.

Equations 15 and 16, and Adaptation with Equations 25 and 26:
We have updated the manuscript to include additional definitions and clarification. we have kept only equations 25 and 26 to eliminaate repetetion .

Computational Complexity Comparison:
In Section 3.3, we have expanded the discussion to compare the computational complexity of our Hybrid JADEDO with both DO and JADE separately. We analyze whether the incorporation of DO stages into JADE (and vice versa) increases, decreases, or maintains the overall computational cost. This comparison is now followed by a brief explanation of any improvements or trade-offs.

Pseudocode and Flowchart:
We have included a detailed pseudocode and a color-enhanced flowchart of the proposed hybrid algorithm in the revised manuscript. 

Boxplot Analysis in Figure 6 (Similar to Figure 10):
In response to your recommendation, we have included the boxplot analysis for the compared algorithms in Figure 6. 

Method's Limitations, Practical Benefits, and Future Work in Conclusion:
We have expanded the Conclusion section to offer a concise overview of the potential limitations and practical benefits . Furthermore, we have outlined future work avenues such as automated hyperparameter initialization, multi-objective extensions, and parallelization strategies.

Minor Issues and Errors:
We performed a thorough proofreading of the entire paper and corrected all minor issues .

Once again, thank you for your constructive remarks, which have significantly enhanced the quality of our work. We hope our revisions meet your expectations and look forward to any further feedback you may have.

Sincerely,
Dr. Ahmad

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors accepted and incorporated all my remarks into the manuscript. I have one remark - when I recommended using some newer DE variants, I thought of variants such as jDE, jSO, LSHADE etc. The variant included in the manuscript by the authors is pretty unknown (and probably not the best-performing counterpart)

Comments on the Quality of English Language

Level of the English seems acceptable

Back to TopTop