Topsis-Mritunjay-102003030 1.0.1

Topsis package for Multiple Criteria Decision Making problems(MCDM) problems

TOPSIS SCORE CALCULATOR

By: MRITUNJAY-102003030

Title: Multiple Criteria Decision Making(MCDM) Using TOPSIS

WHAT IS TOPSIS

TOPSIS is an acronym that stands for 'Technique of Order Preference Similarity to the Ideal Solution' and is a pretty straightforward MCDA method. This is a Python library for dealing with Multiple Criteria Decision Making(MCDM) problems by using Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS).

HOW TO INSTALL THE TOPSIS PACKAGE

pip install Topsis-Mritunjay-102003030

FOR CALCULATING THE TOPSIS SCORE

Topsis data.csv "0.25,0.25,0.25,0.25" "+,+,-,+" result.csv

Input File(Example:data.csv):

Argument used to pass the path of the input file which conatins a dataset having different fields and to perform the topsis mathematical operations

Weights(Example:"0.25,0.25,0.25,0.25")

The weights to assigned to the different parameters in the dataset should be passed in the argument.It must be seperated by ','.

Impacts(Example:"+,+,-,+"):

The impacts are passed to consider which parameters have a positive impact on the decision and which one have the negative impact.Only '+' and '-' values should be passed and should be seperated with ',' only

Output File(Example:result.csv):

This argument is used to pass the path of the result file where we want the rank and score to be stored.

EXAMPLE

data.csv

A csv file showing data for different mobile handsets having varying features.

Model	Storage space(in gb)	Camera(in MP)	Price(in $)	Looks(out of 5)
M1	16	12	250	5
M2	16	8	200	3
M3	32	16	300	4
M4	32	8	275	4
M5	16	16	225	2

weights vector = [ 0.25 , 0.25 , 0.25 , 0.25 ]

impacts vector = [ + , + , - , + ]

INPUT:

topsis data.csv "0.25,0.25,0.25,0.25" "+,+,-,+" result.csv

OUTPUT:

      TOPSIS RESULTS
-----------------------------

    P-Score  Rank
1  0.534277     3
2  0.308368     5
3  0.691632     1
4  0.534737     2
5  0.401046     4