Dear Eric

First of all, there is not a MCDM method that will give you the optimal answer.

What do you mean by 'solar location'. Does it mean finding the location with maximum solar irradiation to install something, like a power plant?

If you use GIS are going tto determine weights using intuition?

Could you clarify which is the first and which the second?

For your information, using FAHP was found useless by Saaty, because he said that AHP was already fuzzy

Thank you very much for the reply.

I am working on 2 papers.

the first paper: determining the optimal location for solar PV power plants in Tunisia. I used the FAHP to assign the weights for the criteria. then applied the TOPSIS to rank the alternative locations.

But I was stuck in the FAHP not knowing how to check consistency of pairwise comparison matrices.

In the second paper, I used the classic AHP with the TOPSIS to determine locations for onshore wind power plants.

I was somehow confused with combining both techniques ...

Dear Eric,

You can use the AHP to determine the weight of the attributes. Also, you can use TOPSIS for ranking alternatives.

You use the weights of attributes when you form the weighted normalized matrix in TOPSIS.

Dear Mir

So, you are going to compute th ecomparative importance of highly technical issues such as insolation, capacity factor, maintenance, cost, etc., using intuition?

Dear Eric

If you are engaged in a power problem, you cannot use AHP in any form.

The reason is than criteria in most MCDM power scenarios are NOT independent, and criteria indepence is a stringent condition in AHP, established by Saaty.

I don't know which is the destination of your paper, but whatever it may be consider that it can be rejected by reviewers or stakeholders because again, it is not the method to apply in power generation

Dear Dr. Munier,

This is an answer to a general question:

How to combine AHP and TOPSIS methods?

Dear Mir

Where is the answer?

Nobody is saying that you can't combine AHP and TOPSIS, as is actually done

Just use the weights from AHP in TOPSIS, but, of course, it could be rejected because you would be using weights that are not realistic

Why don't you use entropy weights and TOPSIS? Nobody can reject this procedure

It seems that you are adding a new question.

Mr. Eric did not ask what method is suitable for his problem.

His question is about how to combine these two methods and also how to calculate the inconsistency ratio.

You are adding some information to his question and trying to answer your question.

I ask Mr.Eric to explain more about his problem and its attributes. Are attributes qualitative or quantitative?

If you use quantitative data such as cost, capacity, etc., I agree with Dr. Munier. You can apply an objective weighting method such as Shannon entropy to determine the weight of attributes.

The data I am using for allocating optimal solar/wind location involve Solar Radiation, wind speed, air temperature, slope, dist. to grid network, roads, and residential areas...

Hola Eric, si se trata de ubicación puedes incorporar metodologías de la teoría de localización, más metodologías de decisiones multicriterio como el AHP resultan de ayuda para realizar determinadas clasificaciones y si es posible hacer híbridos con otras, el aporte valioso del AHP es que te da los pesos de manera justificada.

Dear Henry

El problema de localizacion industrial es tan viejo como el MCDM, y practicamente cualquier metodo se puede usar, siempre que se pueda modelar el problema en forma correcta.

Te agradecere me contestes de donde sacaste que AHP da los pesos de manera justificada.

Decidir por intuicion puede ser importante en un problema personal, pero no en casos como es la localizacion industrial

Si es asi, me agradaria que me instruyas sobre que axioma, asuncion logica o teorema se basa tu aserto

Dear Eric Sassi,

Yes,

For attributes such as wind speed, air temperature, slope, and dist, since you have real data, you can apply Shanon entropy.

I suggest reading the following book to learn more about objective and subjective weighting methods.

Zardari, N. H., Ahmed, K., Shirazi, S. M., & Yusop, Z. B. (2015). Weighting methods and their effects on multi-criteria decision making model outcomes in water resources management. Springer.

I appreciate it