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Mathematical Models for the Design of GRID Systems to Solve Resource-Intensive Problems

Authors: Valeriya V. Tynchenko,Vadim S. Tynchenko,Vladimir A. Nelyub,Vladimir V. Bukhtoyarov,Aleksey S. Borodulin,Sergei O. Kurashkin,Andrei P. Gantimurov,Vladislav V. Kukartsev
Journal: Mathematics
Publisher: MDPI AG
Publish date: 2024-1-15
ISSN: 2227-7390 DOI: 10.3390/math12020276
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The reliance on theoretical performance and reliability metrics for GRID systems without empirical validation undermines the practical applicability of the study. Could the authors provide evidence or real-world data to substantiate these claims?
The proposed multi-criteria optimization models lack a clear discussion of alternative methods or benchmarking against existing approaches, raising concerns about the robustness of the claimed superiority. Addressing how these models compare to others in terms of computational efficiency and outcome quality would strengthen the conclusions.
The omission of a sensitivity analysis for key parameters (e.g., availability rates, migration rates) in the GRID system models makes it difficult to assess their reliability under varying conditions. Could the authors clarify whether such analyses were conducted and, if not, how this omission impacts the study’s findings?
The study’s use of simplified assumptions about node failures and recovery processes in the reliability model could lead to overestimation of GRID system performance. A more detailed exploration of real-world failure patterns would improve the validity of the results.

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3 weeks, 3 days ago

They cite two major foundational papers in genetic algorithms, Schaffer’s VEGA and Fourman’s layout compaction, and claim they were presented at the “First International Conference on Genetic Algorithms” in December 2013.

 
That’s impossible.

 
The actual first conference was in 1985. These are landmark works in the field. You can’t just move a pivotal moment in CS history 28 years forward.

 
This isn’t a typo!! it’s either extreme incompetence or deliberate fabrication. Either way, it torpedoes the whole paper’s credibility. If they’re faking their basic references, why should we trust their models, results, or conclusions?

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