Being a software engineer, I studied two things in soft computing - binary logic and fuzzy logic. Binary logic works on two things only, either yes or no, true or false, zero or one. On the contrary, fuzzy logic gives an alternative to this approa…

Being a software engineer, I studied two things in soft computing – binary logic and fuzzy logic. Binary logic works on two things only, either yes or no, true or false, zero or one. On the contrary, fuzzy logic gives an alternative to this approach, as every real life scenario cannot be catered in binary logic. There may be a condition when you can't be absolutely true or absolutely false. There is a need to give values in range. To make my point clear, I will illustrate the same with some examples.

**Sand Heap Paradox**

Consider a heap of sand. How you will define a heap of sand?

You would say if there is a collection of some 10,000 plus grains of sand, then it's a heap of sand. But what about that collection of sand particles which has 9,999 grains of sand? Isn't it a heap of sand? One has to draw a line to decide when a collection of particles will stop becoming a heap of sand.

Lets say there are three friends A, B and C and their heights are respectively 181 cm, 180 cm and 179 cm respectively. By general observation, I would say that all three of them are tall. But, if by definition, it is decided that any person with height greater than or equal to 180 cm will be considered tall, then what about C? Isn't he tall. Just because he is shorter by 1 cm, isn't it unjustified to call him short heighted?

All these problems arise because we work on binary logic. Real life scenarios are complex and dynamic. You can't be sure all the time and you cannot assign crisp values to anything and everything. That's why fuzzy logic is needed.

Now, enough of explanations (sorry for being too verbose). Let me come to the point.

We all have seen the ruthless nature of application rating introduced by IIM-A.

Let's consider a scenario with the criteria mentioned by IIM-A.

Class X – 88.6 %, Rating Score – 3 (A)

Class XII – 78%(Mathematics), Rating Score – 2 (B)

Graduation – 75.33% (Engineering), Rating Score – 2 (C )

Master's Degree – NA, Rating Score – 0 (D)

Work Ex – 2.5 years(IT), Rating Score – 3 (E )

Application Rating – (AxBxC) + D + E = (3x2x2) + 0 + 3 = 15

For cursed people like me (General Category, Male, Engineer), application rating should be greater than 24 to get a call from IIM-A, irrespective of your CAT score. I would never get into IIM-A, irrespective of how hard I try.

Again, this all happened because of this binary logic. Even if I would have scored 79.99 percent in Class XII or 75.99 percent in graduation or 100 percentile in CAT, I would have got the same rating and ultimately, no call.

**Solution to this problem:**

Lets take the help of fuzzy logic. It says that do not assign absolute values to things. Introduce the concept of range. For example, for class XII, percentage wise rating score is as follows:

Less than 60 – 1

Between 60 and 80 – 2

Above 80 – 3

Lets take these rating scores in decimal as per percentage range, i.e

For 60% - 2

For 70 % - 2.5

For 75% - 2.75

For 78% - 2.9

For 80% - 3

Taking things this way, let's reassign application rating in the previous case:

*Class X – 88.6 %, Rating Score – 3 (A)*

*Class XII – 78%, Rating Score – 2.9 (B)*

*Graduation – 75.33%, Rating Score – 2.75 (C )*

*Master's Degree – NA, Rating Score – 0 (D)*

*Work Ex – 2.5 years, Rating Score – 3 (E )*

*Application Rating – (AxBxC) + D + E = (3x2.9x2.75) + 0 + 3 = 26.295*

Now cursed people may have a chance to get a call from IIM-A as their application rating crossed that threshold of 24 for general category male engineers.

This is something which came in my mind when I was thinking of a solution for my software project. Why to do the injustice with those who are just falling short because of some marks. If IIM-A adopt this approach, then I guess many people who did not get call despite getting a good percentile may get a call.

**Some contradictions and their answer**

Now people would say that if we apply this logic in our exams, then nobody will ever fail. If passing marks are 35, then the person who got 34 cannot be deemed as absolutely fail 😁. He is just partially fail.

I agree with this argument.

But when we give our exams in school and colleges, we know beforehand that if we get less than 35, we are fail. So we study accordingly. Now imagine, some two years down the line, if college or school says that passing marks criteria has changed from 35 to 40, and you got 36, then can you be deemed fail in the retrospective effect?

That's what happen with these selection criteria. If we would have known that getting 75.33 % in engineering is not good enough for IIM-A when we were in college, then we would have worked much harder. But now, we just can't change the score. Why to pay the price, when you are just near the boundary or on the verge of selection.

I wrote this whole theory, not to re-invent selection process but to know where I am wrong in my approach.

I am posting this article with the expectation that someone would give me some real good arguments against this approach. Also like to know how many agree with this solution.