Visual AHP software help video

Visual Guide of AHP software

It’s so easy to work with AHP software; just draw your hierarchical graph, enter pairwise comparison data and observe output report or receive it.

At the first step, enter the name of your project.

For example, this project is done at the manager’s choice and according to the AHP procedure. 

In this part, you can create your hierarchical graph.

For adding criterion or sub- criteria, press the positive button and for deleting criterion (or sub-criteria), press the negative button.

For writing favorite name for criterion, click on the name of the criterion and enter your favorite name. We suggested that you select a short name.

According to the picture, select the setting part (gear) for appearance setting of graph. In this part, you can change the color, shape and other characteristics of graph (this feature will be added soon).

If you have alternative, select “yes” and then, with pressing the button of “adding alternative”, add your new alternative. If you don’t have any alternative, select “no”.

For deleting favorite alternative, mark the negative sign.

Change of name and appearance setting of alternatives is like the criterion part (this feature will be added soon).

In this part, you can complete the pairwise comparison charts that have been created according to the hierarchical graph.

For filling, you should click on each table cell and enter your pairwise comparison number.

It’ been suggested that for preventing of wasting time, enter you data in excel and then, enter the data of every chart with copy and paste.

If you enter a number bigger than 1, it shows the preference of row criteria by column criteria. For example, if you enter number 5, it means that the criteria in the row is five times preferable than column criteria.

If you enter a number between 0 and 1, it shows the preference of column criteria by row criteria. For example, if you enter number 0.25, it means that the criteria in the column is four times preferable than row criteria.

With pressing the button of inconsistency rate, the amount of inconsistency rate is being shown on the above of each pairwise comparison chart.

As you see in the above picture, expert’s part includes:

– Adding expert: if the number of experts is more than 1, you can increase the number of experts with pressing this button. With pressing this button, previous expert will be saved automatically and the new expert will be added.

– Delete: with pressing this button, the existing expert will be removed.

– Save: with pressing this button, the data of existing experts will be saved.

As you can see in the below, expert’s status includes:

– If all of the expert’s data get complete and saved, the status of expert is being completed.

– If all of the expert’s data not completed, the status expert is not completed.

– If an expert be deleted, the status is being removed and you can recover that data in this part.

Mean: with pressing this button, geometric mean of all experts are being shown along with the inconsistency rate of all of the charts of pairwise comparison.

For observing mean, you should complete the data of all the existing experts.

The pairwise comparison bar is exists in the bottom of the page of pairwise comparison bar that shows the degree of preference of selected cell:

– If the number is bigger than 1, it shows the degree of preference of row component on the column component. 

In this example, the row factor (charisma) is doubly preferable than column factor (age).

– If the number is between 0 and 1, it shows the degree of preference of column component on the row component. 

In this part, you can observe the weight criteria/ sub- criteria and alternatives with higher level in the form of charts and graphs. On top of each graph, there is also consistency rate. You can download each graph in different formats.

Also, you can observe and download the hierarchical graph of research.

In the part of download, you can download the output “word” report, excel file of input data, excel file of output data with inconsistency rate. As you can see in the image below, you can select one of the ways of “ideal” and “distributive” for calculating the output weights.