Methodologies and Handling Techniques of Large-Scale Information in Decision Support Systems for Complex Missions

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The  authors discuss the challenges of designing and integrating systems to support, monitor, and execute complex missions. The paper highlights the limitations of past "ad hoc" solutions in national defense and security, and  proposes new methodologies for organizing large data sets and systematically handling operational procedures. By implementing these methodologies, the system aims to improve decision support capabilities for complex missions, ensuring sustainability and adaptability in an ever-changing landscape. The paper emphasizes the importance of structured data organization and the use of a teleological structure to optimize mission objectives and support diverse operational requirements. The proposed methodologies are based on extensive interviews with experts in various domains.

The paper is well written and further details are provided in four appendices to the paper.  It is good contribution to the field of theoretical operations research.

However, my impression is that at this stage this is just a very general theoretical framework for decision making in very complex scenarios. It is not clear to me whether the framework has been applied to real problems (after all, the paper is submitted to Applied Sciences, not Potentially Applied Sciences). I suggest that the authors make it clear in the Conclusion whether or not their framework has been validated in real applications.

The phrase line 44 sounds odd. Perhaps "effective and optimization and" should be removed.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This manuscript aims to propose a novel decision support system for the Complex Mission, especially on a large scale. The authors presented its methodology well and its application simultaneously. The method is worth applying to large-scale complex decision problems such as the problem army and government.  The manuscript is well-written and worth publishing in its current form. 

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have a comprehensive approach in their manuscript to addressing the challenges in designing systems for complex missions, and then aiming to overcome past failures through advanced methodologies and the introduction of CMSSs.

Thank you for the opportunity to read the manuscript, and please allow me to make a few suggestions for the authors.

The authors mention the limitations of traditional DSSs, but they do not thoroughly discuss the potential limitations or challenges associated with the proposed CMSS . I suggest that the authors discuss a little bit more on the potential limitations or challenges associated with the proposed approach (if any), like scalability issues, data privacy concerns, implementation barriers etc.

I understand that the manuscript is already very long, so my next suggestions could be taken into consideration for authors’ next manuscript, for the continuation of their research:

I suggest the authors to conduct empirical validation through simulations or case studies so as to demonstrate the effectiveness and practical applicability of the proposed CMSS framework. I am suggesting this, due to the fact that while the manuscript presents a theoretical framework and detailed methodologies, I believe it needs some more empirical validation through experimental results / case studies etc.

Also, the authors could discuss some more on the practical considerations for implementing the CMSS framework in real-world settings, for example like data integration challenges, system interoperability, stakeholder engagement.

I suggest that the authors try to simplify a little bit the technical language used . I am suggesting this, due to the fact that the manuscript's presentation is highly technical and could be rather challenging for readers without a strong background in decision support systems to fully comprehend.

Furthermore, I believe that more illustrative examples/figures would increase the understanding of the manuscript.

I also suggest that the authors could conduct a more comprehensive comparative analysis of the proposed CMSS framework with other existing approaches /alternative methodologies. This could bring some more light on its advantages but also on the potential limitations.

For authors’ future research, they could also include some other novel methods such as:

-the integration of machine learning algorithms for predictive analytics and decision support within the CMSS framework,

- blockchain technology potentially used for enhancing data security, integrity, transparency within CMSSs,

-human-computer interaction HCI to design user-friendly interfaces and decision support tools within CMSS framework,

- multi-agent systems MAS for modeling complex interactions / coordination among autonomous agents within CMSSs etc.

Author Response

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Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

This study presents a theoretical overview of the methodologies and their procedures that can be used for creating the decision support system. The authors have done a very hard job to collect all necessary data and to describe in detail each algorithm in each methodology. The paper is well prepared and well organized. In my opinion, this paper has a potential to be of interest for researchers dealing with decision-making problems. However, I have observed several drawbacks that should be revised:

1. Since this is an overview of the methodologies and techniques in decision support systems, you should add more literature sources dealing with this scientific field.

 

2. The organization (structure) of the paper is missing. Please include it in the last paragraph of the Introduction section where each Section will be described in one to two sentences.

3. You compensated for the lack of mathematical equations and relations with a comprehensive theoretical description of each methodology. From an engineering point of view, the main focus should primarily be placed on extensive mathematical tools rather than exhausted theoretical explanations. It is very difficult to realize the core of any study through the theoretical examination. I would like to suggest you to analyze at least one of the mentioned methodologies using mathematical formulas. It would be very useful for young researchers to better understand these presented approaches.

4. Surely, during the collecting of the data in the large-scale datasets it is inevitable to make some errors. To overcome this serious problem that can greatly influence the final results it is necessary to include imprecise information about the input data. Is it possible to treat the large-scale datasets as an uncertain environment? Can the input data be described as fuzzy or interval numbers? Can the efficiency of the decision support system be improved in this way? Please, give a discussion about these opportunities.

5. What are the directions of future research? Please add them in the Conclusion section.

 

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 4 Report

Comments and Suggestions for Authors

The authors have corected and revised all suggested comments. The paper looks great now and absolutely acceptable to be published in this Journal.