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I have described succinctly the strengths and weaknesses of some Multiple-criteria decision-making (MCDM) methods, however, I would like if you could help me to write these points for the VIKOR and WSM methods, as well as check if I am writing something wrong of any of the methods already described.

AHP (Analytic Hierarchy Process)

Strengths: It is scalable; its hierarchical structure can easily adjust to fit many complex problems.

Weaknesses: It contains too many pairwise comparisons; it might have problems due to criteria and alternatives interdependence; it can lead to inconsistencies between criteria and classification.

ELECTRE ((ELimination Et Choix Traduisant la REalité)

Strengths: It takes into account the uncertainty and imprecision in the analyses.

Weaknesses: Its process and results can be hard to explain; ranking can make it difficult to directly identify the strengths and weaknesses of attributes.

MAUT(Multi-Attribute Utility Theory)

Strengths: It takes into account uncertainty; it canincorporate references.

Weaknesses: Needs a lot of input data; preferences must be exact.

PROMETHEE (Preference Ranking Organization for Enrichment Evaluations)

Strengths: It requires no assumption about criteria being proportional.

Weaknesses: It does not provide a clear methodology for weighting coefficients.

SAW (Simple Additive Weighting)

Strengths: It allows compensation between criteria; it has simple calculations and it does not require complex computer programs.

Weaknesses: Its final scores do not always reflect the real situation; the result might not be logical.

TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)

Strengths: It is simple; the number of steps remains the same regardless of the number of attributes.

Weaknesses: It has hard-weighting coefficient attribution and attribute judgement.

VIKOR (Vlsekriterijumska Optimizacija I Kompromisno Resenje)

Strengths:

Weaknesses:

WSM (Weighted Sum Model)

Strengths:

Weaknesses:

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The MCDM methods was created to make better decisions when the decision criteria is usually non-quantitive and is needed to create a decision as fast as possible.

Also, there is really no obvious difference between those as anyone can use one or more such techniques to see still which one is already perfect for the problem. It means despite of quantitiv decision making methods like mathematical programming, there is no guarantee to achieve a global solution and the results of the one method might be quite different from another one.

Also, there are many of the papers that compare these methods which can be easily found by googling. E.g:

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