TOPSIS Package
Project description
for: TOPSIS submitted by: Ira Vashisht Roll no: 102017029 Group: COPC2
TOPSIS_Ira_102017029 is a Python library for (TOPSIS).The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method determines the best solution from a set of alternatives with certain attributes. The best alternative is chosen based on its Euclidean distance from the ideal solution. TOPSIS is widely used in various multi-attribute decision making problems such as supply chain logistics, marketing management, environmental management or chemical engineering. Despite the extensive use of this method, there is no free and open-source software (FOSS) for TOPSIS with comprehensive post-analysis extensions
Installation
Use the package manager pip to install Topsis-Ira-102017029.
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 (+,-)
INPUT
And using this package in Python as :
import topsispy as tp
a =[
[250, 16, 12, 5],
[200, 16, 8, 3],
[300, 32, 16, 4],
[275, 32, 8, 4],
[225, 16, 16, 2]
]
w = [0.25, 0.25, 0.25, 0.25]
sign = [-1, 1, 1, 1]
tp.topsis(a, w, sign)
The package can be used via commandline as :
$ python [package name] [path of csv as string] [list of weights as string] [list of sign as string]
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 = [ + , + , - , + ]
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 |
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