Analytic Hierarchy Process (AHP) 

Good day professor. @5:58 for normalizing the matrix. In the Camera column, you used 7 as the divisor. was that a mistake? because the total for camera shows 5.83. Thanks for the video sir

Thank you sir for your explanation! This is the first resource I got where I could understand all the terms of AHP. You have saved me !

The best AHP explanation I have ever seen! Thank you very much!

U came back to your video to say thanks for making this. I saw much stuff on the net for AHP but this is the top simple way of teaching you told. It helped me a lot. Really thanks

Thank you very much Professor. This is the simplest step that I can understand!

Thank you for very simple and extremely helpful explanation! Keep up with excellent work!

Thank you for saying "Random Index" with such flourish such that I will never forget what RI stands for

Thank you, Professor! Keep up the good work!

Thank you so much!! My final is this Monday and this made me feel a lot better

Well done Sir, this is the best explanation i came across so far. Thanks

Thank you very much, this method will help me doing my project on a seminar.

Thank you so much Sir...i have solved my project after watching your video....thanks again..May GOD bless you

Good day This must be the best explained weighting video so far.

Thank you for this quick and super useful tutorial!

Thanks Manoj for a very easy explanation of AHP, looking forward to follow more videos on different models... cheers :)

Thank you!! You explained it so clearly and concisely.

Very informative!! Nicely explained!! Thank you very much!

Thank you so much for this tutorial. Its clear and easy.

clean & Clear. couple of questions 1. What is i have more than 15 criteria to evaluate ? -> what will be the RI value for n > 15 2. how about selecting the alternatives ? -> after validating the criteria we should look at choosing alternative right ?

hi Manoj, very understanding your explanation. thanks for the video, since in my master degree I’m studying this topic right now And I was a bit confused, now is crystal clear.

Thank you sir for allowing me to have better understanding on AHP.

Thank You for this video. I have finally understood the AHP concept from this after a struggle of many days at many places. I have cleared all my confusion as to how I can proceed with my research.

Very well explained. Thank you for making this process so clear

Thanks for posting this video. It has been informative. Would you please explain in a bit more detail how RI is obtained? I'm a bit confused on that part. Thank you.

So clear and so helpful. Thank you Sir!

Thank you so much 👍 I was trying to understand the matrix calculation ... finally I found it

Such a neet and clean explanation..this hepls me to clear my concepts...thank you so much sir...May god bless you..keep helping us whenever you have time .

This the excellent lesson I have ever seen on AHP. Thanks. Please make a video on Delphi.

Thanks a lot! You’ve saved my day.

Totally awesome video.. Very easily you explained everything.

Hello! I am writing a graduation paper, part of which touched on this method, and unfortunately there are practically no videos on this topic in Russian(((( You helped me a lot, thank you!!!

Thank you for the video. It was descriptive as well as precise.

Excellent sir ..... I can't say how much I helped from your vedio 🙏🙏🙏🙏🙏🙏

I like the explanation again :) thank you. I wanted to add that there are different methods to calculate the criteria weights. one of the most common ones is the eigenvalue.

Very lucidly explained, thank you

This video is really useful. Thanks for the good explanation

Thanx, it was really well explained without any complexities.

This is a great tutorial; but I think you may have an error in the fractions in your pair-wise comparison matrix. In the Camera column, the sum is 5.83, but you have divided through by 7. That makes a difference in the calculations going forward.

Good day Professor. This video is well presented thank you. I used the same in actual for supplier KPI however CR resulted to more than. 10 meaning it's not consistent but I painstakingly followed as instructed. How to resolve inconsistency?

This was immensely helpful. Thanks Sir .

Thank you sir for such a informative vdo ...very useful and well understood

Thank you. Just what I was looking for :)

Thanks alot sir....u have explained it very nicely and easily

Hi Manoj, this is great, thanks for your detailed explanation. How do you calculate the Random Index figures?

Excellent video Sir. Very nicely explained.

you save me, professor. I really appreciate you!

Thank you so much for the video. I'd like to ask, what if the CI and CR turn out to be negative? Would that also mean that we can not use selected criteria?

Great video. Helped a lot! Thanks!

Thank you sir. Great way of explanation. Please clear my doubt that-From exam point of view how can we assign weights in the initial matrix to get consistent value of CR(CI÷RI)?

Excellent Video Sir. Thanks a lot.

Thanks for a great video. I have a question, is the sums of criteria weights must equal 100% or not?

Thank you so much for all your information 👏🏽👏🏽👏🏽

sir your videos are very informative and easy to understand.

Thank you so much, professor.

Thanks. It is really helpful and easy to understand.

sir you just have saved someones life!

Thank you for uploading this video. It really helped! I would like to ask why you didn't take into account cost columns - ones we want to have the lower value as beneficial, not higher - in normalization part? When it was considered, consistency_ratio changes pretty obviously. Thanks in advance for any response

Thanks dear it's really helpful for us ........

Thanku .It is really usefull section

Professor Manoj, I would love to watch Fussy TOPSIS in your coming up videos. thanks

Thank you for the video Proffesor!

Thanks for Ahp calculation.

Thank You for your knowledge

Thank you very much for this clear explanation

This was awesome. Thanks.

Thanks Prof. I have 10 decision makers and my research requires all their results to yield a weight for each parameter, how do I go about that?

Thanks for the exolanation sir, but I have a question when the alternative on the third level just got 1 n don't have indicator to compare with, then just let it 1 multiplied by weight from 2nd lvl?

Good explaination. Thanks.

Quite easy to follow. Thanks alot Manoj

Thank you.. It was really helpful.

very nice and clear explanation. Manoj, do you have any literature published that have this explanation and which I can reference in my thesis?

Thank you professor, you saved me

Thank you very good explanation.

very well described, thanks

Explained very well sir!

Great video sir!

Thank you for the explanation, I have a question. I applied this method for the first time and I found a negative value for the consistensy index (C.I.), how can i fix that ?

Thank you sir. It was a nice presentation.

Just wanna say thank you sir, if u have matlab read this and solve problem on excel, that would be more than just great.

thank you professor very useful lesson

Thanks for the video.

Thank you sir. Its very useful for me.

thank you Sir for sharing the video, just i have a question to ask is how can calculate the risk level by using AHP method ? i really need your answer

Thank you! It helps me! :)

Hi, thank you so much for your explanation but may you tell me from which references you could get this point that we can compute the consistency index and Geomean in Fuzzy AHP

Great video! Could you please tell me what's lambda max? I am unsure about why we use that in the equation.

Thank you..... it is clear

Great explanation!

thank you, sir, for this very informative video, but can you suggest some ahp software that will help in this regard for the solution.

Thanks very much prof....

THANKS FOR THE VIDEO SIR..

Very good. Thank you.

Wonderfully explained

well explained! Thank you

Many thanks professor manoj. Looking for another your videos.

thanks so much Prof Manoj. This can be done in excel

Hi Manoj, Are there any statistical methods available for ranking or selection purposes, specifically when we have hundred's of features.

really good explanation

Keep up the good work!!!

Simple and easy to understand