Dear Nayan!

Similar cases from the author of this method T. Saati:

1) Saaty, Thomas L.; Peniwati, Kirti (2008). Group Decision Making: Drawing out and Reconciling Differences. Pittsburgh, Pennsylvania: RWS Publications. ISBN 978-1-888603-08-8.

2)Saaty, Thomas L. Decision Making for Leaders: The Analytic Hierarchy Process for Decisions in a Complex World. — Pittsburgh, Pennsylvania : RWS Publications, 1999-05-01.

3)Saaty, Thomas L. The Hierarchon: A Dictionary of Hierarchies. — Pittsburgh, Pennsylvania : RWS Publications, 1992. — ISBN 0-9620317-5-5. 496 pages, spiral bound. Each entry includes a description and diagram of an AHP model; the models are grouped in categories: educational, government/public policy, government public/strategy, health military, non-profit, personal, planning, political, etc.

Best Regards, Andrey Khorolskiy

Dear Nayan!

Similar cases from the author of this method T. Saati:

1) Saaty, Thomas L.; Peniwati, Kirti (2008). Group Decision Making: Drawing out and Reconciling Differences. Pittsburgh, Pennsylvania: RWS Publications. ISBN 978-1-888603-08-8.

2)Saaty, Thomas L. Decision Making for Leaders: The Analytic Hierarchy Process for Decisions in a Complex World. — Pittsburgh, Pennsylvania : RWS Publications, 1999-05-01.

3)Saaty, Thomas L. The Hierarchon: A Dictionary of Hierarchies. — Pittsburgh, Pennsylvania : RWS Publications, 1992. — ISBN 0-9620317-5-5. 496 pages, spiral bound. Each entry includes a description and diagram of an AHP model; the models are grouped in categories: educational, government/public policy, government public/strategy, health military, non-profit, personal, planning, political, etc.

Best Regards, Andrey Khorolskiy

Search for articles about AHP

Dear Nayan,

The simplest solution to your problem is conducting some kind of "primitive" normalization:

I. Make new empty table 54 Alternatives and 6 criteria

II. Calculate the normalized table by some of several types of normalization - choose one:

1) Normalization 1:

a) for beneficial criteria - divide each value with the highest value in the column

b) for non beneficial criteria - divide minimal value in the column with each value

2) Normalization 2:

a) for beneficial criteria - calculate (1- minvalueofthecolumn/eachvalue)

b) for non beneficial criteria - calculate (1- eachvalue/highestvalueinthecolumn)

3) Normalization 0-1

a) for beneficial criteria - calculate (eachvalue-lovest)/(highest-lowest)

b) for non beneficial criteria - calculate (highestvalueofcolumn-each value)/(highest-lowest)

4) Euclidean normalisation

First - convert non beneficial criteria to beneficial - calculate the reciprocal value

Second - for each criterion, calculate Eucledian constant - it is a root of sum of squares of all values

Third - divide each value from the table with related Euclidean constant

III: After the normalized matrix is calculated, for each alternative multiply the criteria weight with normalized value, and sum those products for all criteria (SAW method - simple additive weighting).

The alternative with the highest sum of products is the winner.

The alternative can be conducting the Electre method - there is a free tool called Sanna (Excel addin for that). Also, the AHP is the alternative.

There are other types of normalization - normalization by sum, normalization by absolute value...

If you need additional help in Excel, let me know.

Applying several types of normalization and comparison of the results can be some sort of sensitive analysis.

Thanks a lot, Nikolas. This is how premitive normalization looks like. PFA

I am glad you did it! :-)

Nikola Kadoić Could you please share citations for the "primitive normalization" that you have mentioned? I would definitely like to add this in my Thesis work!

Sorry for late reply. What you need is here in Table 1

Conference Paper Normalization Techniques for Multi-Criteria Decision Making:...

Thanks a lot Nikola Kadoić Appreciate it.

Best regards