# 151

Dear Yinan Wang , Heng Chen, Shuyuan Zha , Lanxin Fan, Cheng Xin, Xue Jiang and Fan Yao

I read your paper.

Benefit Evaluation of Carbon Reduction in Power Transmission and Transformation Projects Based on the Modified TOPSIS-RSR Method

My comments

1- In the abstract you say “Subsequently, weights were assigned to these indicators using a combination of the fuzzy analytical hierarchy process (FAHP) and the entropy weight method (EWM) through both subjective and objective methods”

I would like to remind you that Saaty himself criticized the use of fuzzy in AHP, since, as per his words, AHP already is fuzzy.

2- Which is the principle of minimum information? What are the transformation projects?

3- Do you speak of the benefits of CO2 reduction from the environmental point of view or from economics?

4- In page 2 what leveraging and advantage mean? What advantage are you talking about?

5- Page 2 “However, due to the sole reliance on subjective evaluation methods, there is an issue of insufficient persuasiveness in the evaluation results”

Of course, there is insufficient persuasiveness since the AHP lack of reasoning and producing invented weights, cannot convince people that reason that pair-wise comparison and arbitrary weighting is illogical and defies common sense. They do not need mathematics to reach this conclusion

6- You speak of validation which is something inexistent, because you do not have a yardstick to compare results to.

7- “Information entropy quantifies the degree of dispersion among criteria”

This is inexact. Entropy DOES NOT qualify degree of dispersion among criteria, but among the set of values inside each criterion

8- “SIMUS method utilizes linear programming techniques to automatically allocate resources optimally, fulfilling all criteria”

Incorrect. SIMUS does not allocate resources. What is does is to use known resources according to their availability and in so doing, objectives are fulfilled differently

9- Fig1 shows that you apply fuzzy to AHP. You are not the first, however think about this. If you apply fuzzy, a useful tool, to two or three arbitrary weights obtained by AHP, the crisp values that you will obtain are a media of a set of arbitrary values, representing the DM estimates. What is that good for? If you apply fuzzy to reasonable obtained weights, using fuzzy makes sense, but certainly not with invented values.

10- Page 5 “” are combined and weighted using a combination of FAHP and EWM. For qualitative indicators such as Social Benefit C, sub-indicators like “Impact on residents’ income” and “Impact on residents’ employment” are weighted using the FAHP”

Too bad that you did not take into account that the indicators you mention are not independent, consequently, AHP cannot be used because it only works with independent criteria. This was specifically pointed out by Saaty.

11- Page 5 “The internal rate of return (IRR) is the discount rate when the cumulative present value of the net cash flow over the life cycle of the power transmission and transformation projects is zero. IRR is a key indicator for assessing the profitability of power transmission and transformation projects. If the IRR exceeds zero, it indicates that the project is economically”

If the IRR is zero nobody will investment a cent. The IRR corresponds at the rate where the Net present Value (NPV) is zero, which is different. So, for you an IRR of 0.2% is good for a project?

Dear researchers, as you can see your article is based on false premises and concepts, from my point of view, and for that reason I stop the reading and my comments here.

Anyway, I hope that my comments may help

Nolberto Munier