Topsis package for Multiple Criteria Decision Making problems(MCDM) problems
Project description
Topsis Score Calculator
Project-1 (UCS654)
Submitted By: Rohan Grover
Roll no: 102003029
Group: 3COE2
Topsis-Rohan-102003029 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).
Installation
Use the package manager pip to install Topsis-Rohan-102003029.
pip install Topsis-Rohan-102003029
Usage
Enter csv filename followed by .csv extentsion, then enter the weights vector with vector values separated by commas, followed by the impacts vector with comma separated signs (+,-)
topsis sample.csv "1,1,1,1" "+,-,+,+" output.csv
Example
sample.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 sample.csv "0.25,0.25,0.25,0.25" "+,+,-,+" output.csv
output:
| Model | Storage space(in gb) | Camera(in MP) | Price(in $) | Looks(out of 5) | Topsis Score | Rank |
|---|---|---|---|---|---|---|
| M1 | 16 | 12 | 250 | 5 | 0.534277 | 3 |
| M2 | 16 | 8 | 200 | 3 | 0.308368 | 5 |
| M3 | 32 | 16 | 300 | 4 | 0.691632 | 1 |
| M4 | 32 | 8 | 275 | 4 | 0.534737 | 2 |
| M5 | 16 | 16 | 225 | 2 | 0.401046 | 4 |
Other notes
- The first column and first row are removed by the library before processing, in attempt to remove indices and headers. So make sure the csv follows the format as shown in sample.csv.
- Make sure the csv does not contain categorical values
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