I have a set of generic product features/attributes defining a set of functionality requirements (my “wants/needs"). Any number of available products potentially satisfy my requirements at some given/calculable cost. My objective is to find the best match of my requirements at the lowest cost (normally financial). I need some direction guidance on using an appropriate methodology and technique(s) which I can study/learn and apply to an automated decision making process. I thank you in advance for any help you are able to provide.
closed as unclear what you're asking by MichaelT, GlenH7, Robert Harvey, Bart van Ingen Schenau, Greg Hewgill Dec 5 at 4:31
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Well, correlation is your friend.
Make an array of your needs and give them a number out of 10 in accordance of their importance to you. Now, make similar array for each of the products associating with them your needs and give a number to each according to how well they fulfill your needs. Now we have two arrays, one of your needs and other one of how each product fulfill your needs.Now, all we have to do is to find correlation between the two arrays.
For example, Suppose I need to buy a laptop and I have two products to choose from. My needs are memory space and speed. And when I rate them as per my priority, my array becomes Me = array('memory space'=>7 , 'speed'=>4) Now I go to each of the two products and rate them as follows: Product1 = array('memory space'=>5 , 'speed'=>7) Product2 = array('memory space'=>8 , 'speed'=>6)
Now apply the following formula with your array and each of the product array. And you'll get a value varying from -1 to +1. The value closest to +1 is your best choice.
Correlation(r) =[ NΣXY - (ΣX)(ΣY) / Sqrt([NΣX2 - (ΣX)2][NΣY2 - (ΣY)2])] where N = Number of values or elements X = First Array Y = Second Array
You can find the examples on how to determine correlation between two arrays on internet.
Hope, this helps.