Topsis-Rakshita-102303498 1.0.4

TOPSIS implementation for MCDM problems

Topsis-Rakshita-102303498

Project Description

Topsis-Rakshita-102303498 is a Python package that implements the
Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS),
a widely used method for Multiple Criteria Decision Making (MCDM).

This package allows users to rank alternatives based on multiple criteria by providing a CSV file, weights, and impacts through the command line.

What is TOPSIS?

TOPSIS is based on the concept that the best alternative should have:

• the shortest distance from the ideal solution, and
• the farthest distance from the negative-ideal solution.

Installation

Install the package from PyPI using pip:

pip install Topsis-Rakshita-102303498

Usage

Run the package from the command line:

topsis input.csv "1,1,1,1" "+,+,-,+" output.csv

Arguments

input.csv : CSV file containing alternatives and criteria
weights : Weights for each criterion (comma-separated)
impacts : Impact of each criterion (+ for benefit, - for cost)
output.csv: Output CSV file containing TOPSIS scores and ranks
Input File Format
First column: Alternatives
Remaining columns: Numeric criteria values
No categorical data allowed in criteria columns

Example Input (sample.csv)

Model,Storage,Camera,Price,Looks
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

Output

The output file will contain two additional columns: Topsis Score Rank Higher score indicates a better alternative.

Notes

The first column is treated as an identifier and not used for calculations. All criteria values must be numeric. Weights and impacts must match the number of criteria columns.

License

This project is licensed under the MIT License.