**A Pictorial Guide for the Fuzzy vikor Online Software **

Working with fuzzy VIKOR software is very simple: (1) Define the number of alternatives and the number of criteria (2) Select /create the fuzzy scale (3) Enter the decision matrix data (4) Get the full output

**1. Enter the project name**

First of all, enter your project name.

For example, in this project, the fuzzy VIKOR method is used to select the best college.

**2. Project Specifications****
**** **

Here, you can define the number of alternatives and the number of criteria and the value of the group utility.

**Criteria:**

To select the desired name for the criterion, click on the criterion name and enter your own desired name that is short to write.

Enter each criterion in the column of the table, and then click on the button “Create Criterion Table”. This will create a table of criterion specifications.

In the criterion table, you can enter the name for criterion, criterion type and the fuzzy weight of the criterion. The criterion type can be either positive or negative, which must be denoted by the plus sign (+) or the minus sign (-) in the criterion table. The fuzzy weights can be denoted as l, m, u, which represent the lower, middle, and upper values, respectively.

Note that if the weight of your project is a definite number, l, m, and u can be defined by a number. For example, if the weight of criterion is 0.3, select (0.3, 0.3, 0.3) in the software.

**Alternatives:**

If you want to choose the desired name for the criterion in name column, enter your desired short name.

**Group Utility**:

The group utility value lies between 0 and 1, which is assumed to be 0.5. Click on the link “What is group Utility” in the software to get familiar with this variable.

**3. Select /create the fuzzy scale****
**** **

Here, you can select or create your own fuzzy scale from a list of default fuzzy scales.

You can select your own default fuzzy scale from a list of scales in the list.

If you tend to create your own scale, click “Create your Scale” and create your own scale in the table.

To create a new scale, you need to enter your own verbal expressions and fuzzy triangular numbers. A triangular fuzzy number can be denoted as ( l , m , u ) , where l and u stand for the lower and upper values of fuzzy numbers, respectively, and m for the middle value.

As shown on the picture, you can easily edit a scale

**4. Enter pairwise comparisons**

Here, you can fill the pairwise comparison matrices created based on the hierarchical chart.

Notice that in the pairwise comparison matrices, **the codes that appear in the scale table** need to enter. (A code represents a verbal expression, for example, code 1 implies equal importance)

To fill the pairwise comparison tables, simply click in each cell of the matrix and enter your own pairwise comparison number.

It is recommended that you insert codes in Excel in order to avoid wasting time, and then copy and paste tables from Excel at once.

If a row criterion is more important than the column criterion, enter a positive number. For example, if you enter the 5, the row criterion is 5 times more important than the column criterion.

If a column criterion is more important than the row criterion, enter a negative number. For example, if you enter – 4, the column criterion is 4 times more important than the row criterion.

By clicking on the “Inconsistency Ratio” button, the inconsistency ratio can be displayed at the top of each pairwise comparison matrix**.**

As you can see from the picture above, experts include the following:

**Add Expert**: If there several experts, you can increase the number of experts by clicking “Add Expert”. By clicking on this button, a previous expert will be automatically saved and the new expert will be added.

**Delete Expert**: By clicking “Delete Expert”, the current expert will be deleted.

**Save Expert**: By clicking “Save Expert”, the current expert data will be saved.

As you can see in the picture below, the status of experts include the following:

If all the expert data are completed and stored, the expert’s status is “completed”.

If all the expert data are not completed, the expert’s status is “incompleted”.

If an expert has been deleted, the expert’s status is “deleted” and you can retrieve the data.

**mean**: By clicking on the “mean” button, the fuzzy average of all the experts’ judgments along with the inconsistency ratio for all of the pairwise comparison matrices will be observed. (How to calculate the meanis described by a link in the existing page)

To observe the average, the data of all current experts needs to be completed.

There a scale bar at the bottom of the screen that displays the preference value of the selected cell and you can change the pairwise comparison number using the scale bar tab.

If the entered number is positive, the row component is preferred over the column component.