Dear Seyed

I have been publishing in RG for years about the not so new SIMUS method (2011) that proposes solving MCDM problems through a methodology never employed before and used in solving hundreds of mostly complicated projects in many different fields.

Fundamentally it strictly works with the data provided by the scenario, with criteria defined by the DM, but without weights or preferences of any kind, and thus the result is independent of the DM ; however, its analysis strongly depends on the DM, because he has a paramount role in examining the result and changing, amending or even rejecting it, if he considers necessary, but supported by reliable and accurate data produced by the method.

The latest advance, perhaps in 2013, since I don't remember the date exactly, was IOSA, a SIMUS' extension to perform sensitivity analysis, again using a completely new approach since it does not work with criteria 'weights' but with criteria marginal utilities, generated by SIMUS.

The advantage of IOSA is that the software draws the total utility curve for each criterion, as per the DM decision, and this is an exact, not approximate curve, because it is generated by considering mathematically optimal values for the criteria marginal utilities.

As far as I know the EXACT drawing of these curves has never been done before at least not in the MCDM environment, although there was a pioneer work form Keeney and Raiffa, back in 1976 with MAUT, but using personal appreciations and not the exact marginal utilities. In IOSA this is done automatically, since the DM only need to enter his preferences regarding the objective to analyze and the criteria

Both SIMUS and IOSA are free and can be downloaded from the Internet.

The pioneers universities are the Valencia Polytechnic University (Spain) and Universidad Nacional de Cordoba (Argentina)

The latest book of mine, detailing the shortcomings of the actual systems in MCDM and how to correct them using SIMUS/IOSA, will be published by Springer in New York, possibly next month.

سلام

روشهای تصمیم گیری جدید زیاد هستن

توی لینک زیر آورده شده

https://sanaye20.ir/%D8%B1%D9%88%D8%B4-%D8%AA%D8%B5%D9%85%DB%8C%D9%85-%DA%AF%DB%8C%D8%B1%DB%8C-%DA%86%D9%86%D8%AF-%D9%85%D8%B9%DB%8C%D8%A7%D8%B1%D9%87-madm/

Dear Seyed,

It depends on your paper or work but according to my experience, you can use TOPSIS or FAHP in your paper, i have 3 paper about decision making that papers are accepted in valid journal (i use TOPSIS and FAHP)

Sincerely,

Mohammad Reza

Omega, Mathematics, Symmetry journals

Dear Sayed,

I think that the most recognizable, worldwide known professor specialized in MCDM is Edmundas Kazimieras Zavadskas . Following his achievements, positions he holds, you will find a lot of well- known names, new methods, etc. I personally admire the achievements of Dragan Pamucar , Željko Stević , and their cooperating team.

MCDM can be divided into 2 phases. Assessing the decision-maker's needs and choosing the solution fitting the needs possibly the best.

For the needs' assessment, the following 3 methods convince me:

AHP

Simos

Article Elicitation of criteria importance weights through the Simos...

and FUCOM

Article A new model for determining weight coefficients of criteria ...

I can't assess which method for the second stage is the best. It seems it depends on the problem to be solved. What I've found important, that considering cost or issues in any MCDM method influences the result much. A high cost may significantly lower the rank of e.g. technically the best solution (and then it could be committed).

Not to allow for that, it is better to analyse the cost issues after the MCDM method is applied. Then, based on non-monetary criteria, we can choose the best solution which is also affordable. It was described as MCDM-CCAF procedure in

Article Pareto Optimal Decisions in Multi-Criteria Decision Making E...

best regards

Hubert

Hello ., Multi Attribute Decision Making covers wide range of Technics in Operation Researchs. Depends on Data availability,types of data (& granularity : continuous/discrete data) and uncertainty factor we may choose the right technic:

Here is a summary of Technics ( Summary of references can be found in :

Tzeng G, Huang J (2011) Multiple attribute decision Wiley-Blackwell making methods and application, CRC Press

Hwang, C.L., and K. Yoon. (1981) Multiple attribute decision making, methods and applications, Lecture Notes in Economics and Mathematical Systems, Vol. 186, Now York: Springer-Verlag

There is a broad range of MCDM techniques reported in literature that have both common origin and goals; yet some of these might differ in principle methodology, core structure and model development process. Thus, different MCDM approaches may yield varying results for exactly the same problem .

The most popular classes of MCDM can be summarized on the basis of their methodological concept of scoring methods (Multi attribute utility theory, or MAUT), outranking methods (PROMETHEE and ELECTRE), compromising method (TOPSIS) and eigenvalue method (AHP). The methods are organised according to their modelling effort which defines the richness of the output. MAUT and AHP generate the most complete form of ranking for each alternative associated with its global score; while TOPSIS and PROMETHEE provide a preliminary form of ranking, including a short list of feasible solutions which may not necessarily be supported by a comparable score. High-effort modelling approaches can effectively include a hierarchical structure and interaction of the criteria in each layer to create relative a ranking score; while in low-effort approaches the performance score of each alternative are measured individually.

Dear Kamran

I am not sure I agree with 'The methods are organised according to their modelling effort which defines the richness of the output', even when you use the very true sentence in small cap, attributed to Alessio Ishizaka . The methods are not organised according to it, but on the utility concept, outranking, distance, and in mathematical programming.

Could you please explain the meaning of your sentence 'MAUT and AHP generate the most complete form of ranking for each alternative associated with its global score', and also 'while TOPSIS and PROMETHEE provide a preliminary form of ranking, including a short list of feasible solutions which may not necessarily be supported by a comparable score'?

I agree with your last sentence, although I am lost with this part

Thank you for your clarification

Dear Hubert

I coincide with your opinion, whatever, I understand that it is not what the DM needs, but what the scenario demands.

It is not a personal problem, - unless it is really personal - but a scenario that exceeds his personal preferences.

Really, I don't understand that you prefer AHP for this, when in this method the DM determines criteria weighs IGNORING which are the alternatives these same criteria must evaluate. I would very much appreciate it if you can clarify this contradiction

Your second phase makes sense, but remember that the solution that better fits, is a consequence of a representative modelling of the scenario, therefore, I believe that the DM must choose the MCDM method according to this representation

The fact that the reviewer is asking you about the method to use, is correct, and proves my second point

Dear Adis

If a method is good, why shouldn't it applied for other authors?

I can't understand your expression of 'come to life'. In my opinion, a method that offers definite advantages over the existent, will be used and possible preferred by many people.

Maybe many methods were and are developed by groups in universities, but that is not a norm. Sometimes that is the effort of only one person

Regarding publishing papers' there are many that are published and that don't resist the minimum examination, just examine por instance how many papers are published using AHP, with scenarios where the criteria are related, and as you probably know, that is unacceptable, since Saaty himself said that AHP can't be used when criteria are not independent .

Even FAHP is wrong, since Saaty said that AHP is already fuzzy. However, there are hundreds of papers publishing problems 'solved' by AHP that the journal reviewers accepted.

I am afraid that your last sentence is difficult to understand. If a reviewer is asking you why you use a certain method, he is certainly right. For instance, in a problem which its structure is NOT hierarchically lineal, you can solve it by ANP, PROMETHHE, TOPSIS or any other method, but not by AHP

in my humble opinion without an objective validation or reference point, something cannot be valuable simply because it is new. Moreover, something cannot be judged solely on its potential ability and capacity. The result is very important, so the generated value cannot be ignored.

I agree with Mahmut in a 100%

Theory and Application of Hypersoft Set

Neutrosophic operational research

Are the latest books for MADM and MCDM

Dear Mir Seyed Mohammad Mohsen Emamat

I combined DEA and MCDM methods, please see the attached DOI

DEA (CCR-BCC-SBM) + AHP

Article A Two-Stage Multiple Criteria Decision Making for Site Selec...

DEA Window + Fuzzy TOPSIS

Article Assessing Renewable Energy Production Capabilities Using DEA...

Dear Thanh-Tuan Dang

Thanks for sharing

Muhammad

Are you sure that the books you mention are the last books in MCDM?

Please check the below link. This may help you.

http://mcda.it/

Dear Partha

Thank you very much for your reference to the paper published by Wątróbski.

I read and found it very important, very clearly written, and with lots of fundaments

I am sending you a copy of this paper where I highlighted those remarks that for me are important.

However, I am surprised that it does not mention probably one of the latest methods in MCDM, as is SIMUS, however, it explains in certain detail and using a clear mathematical language, most of the methods, something that was also done by many papers.

In general, I agree with the whole paper concepts, however, they estimate that their paper is the first to contemplate the problem of selecting a method.

I am afraid that I don’t concur with that, since back in June 2019 I published in RG a very similar matrix procedure, consisting of 10 methods in columns, which can be enlarged as you want, and 54 different characteristics of projects. It really surprises me that in Wątróbski paper, only 6 characteristics are considered to select a project, and however, a large number of methods, when in reality it does not matter the number of methods, as much as the number of characteristics they need to satisfy.

In my method, you can get a quantitative value for each method, according to the necessary characteristics, and therefore, it is easy to select the winner or winners.

My method was published in a book of mine in February 2020.

I am far of questioning what method was developed first; really, that is irrelevant. The two methods follow the same matrix structure, which is natural, but that is where coincidences finish since Wątróbski’s method is very different from mine.

The paper does not explain what are I,P,Q,R,S when taking binary relations

Nolberto Munier Sir

I am very much new to this world. I agree with your points. I am discovering all the possible MCDM methods, their pons and cons for the decision-making processes. In the end, every method gives either ranking, sorting, grouping and prioritising alternatives. Thank you for sharing your method, SIMUS; I will go through this method.

Thank you Partha

I recommend this paper https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29CO.1943-7862.0001418

Dear Giuseppe

Thank you for the recommendation of a paper.

I tried to access it but I couldn't because I am not a member of ASCE, then, I have to be constrained to the abstract

With all respect, I think that the mere title is incorrect; there is no optimization possible in MCDM, because of contradicting criteria

I am a critic of AHP because if it is true that is the most used method, it is also considered the worst for many reasons. It is too naive to be applied to serious problems.

For instance, are you assuming that in construction, a criterion like a type of building, or its height, or its purpose, especially in a seismic environment, is independent of the size of the concrete foundation, or independent of the geological characteristics of the soil? Since it is not, you can't use AHP that considers all criteria independent

Of course, I don't know how your O-AHP method works, let alone how you use mathematical programming, albeit probably to compute criteria weights. For this reason, and for the sake of many users of AHP, it would be interesting if you can give us a short introduction to how the method works

I am afraid that you can't say that 'The validation benchmark tests show that the O-AHP exhibits the same effectiveness of the standard AHP', because at present there is not an MCDM method that can be validated, simply because we don't know which the 'true' result is. In addition, you are comparing the result of your method with the result from AHP, as if it were the paradigm of the correct solution

Thank you