LQR-Based Sparsification Algorithms of Consensus Networks

Round 1

Reviewer 1 Report

The article presents LQR-Based Sparsification Algorithms of Consensus Networks.  The structure of the paper is good. The structure of the paper is good. But to be publishable it needs major revision in presentation and to be more clear and usable for the researchers in the field, there are some issues should be resolved to make the article publishable, otherwise the work should be improved and resubmitted.To improve the quality of the article, the authors should follow the given comments: 

In abstract should be mentioned:

• 1. what is the base of the three algorithms,
• 2. why they are chosen and
• 3. what is their differences and
• 4. specifically what is the result of the comparison of the algorithms.
• 5. The related works listed in the introduction should be specifically mentioned their connection with the topic of the paper, it is good to tabulate them in a table.
• 6. Summarize the optimization problem formulations in a table of subjective function of Constraints.
• 7. Is it linear or non-linear optimization.
• 8. discuss the possibility of using nature-inspired metaheuristic algorithms for optimization on this problem. In this regard, nowadays, metaheuristic optimization has drawn the attention of researchers in a wide range of industrial applications, so they should be mentioned, especially the variants of GA as "New Crossover Operators for Real Coded Genetic Algorithm (RCGA)", "Genetic Algorithm Based on Enhanced Selection and Log-scaled Mutation Technique". Besides, very recent techniques inspired by Mendel's rule of heredity have been suggested as "Mendelian Evolutionary Theory Optimization Algorithm"(2020) which is by inspiration from Mendel's rules of heredity. 

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 2 Report

Globally, the manuscript is very well written and organized. However, there are some minor English errors that must be corrected; please refer to the attached commented document where the majority of these errors are highlighted in yellow.

As such, my recommendation is to accept the manuscript in its current form, and publish it after these corrections.

Comments for author File: Comments.pdf

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

As the authors have revised the paper well and followed the reviewers' comments in detail, the work is qualified for publication.