TOPSIS

Submitted By: Anirudh Bansal

Key Features:

TOPSIS Algorithm Implementation:

This pacakge incorporates a robust and efficient implementation of the TOPSIS algorithm. It considers both positive and negative ideal solutions, calculating the relative closeness of alternatives to the ideal solution.

The package is designed with a user-friendly interface, allowing users to input their decision matrices easily. The library handles the complexity of the TOPSIS method while providing a simple API for users.

Customizable Weights:

This pacakge enables users to assign different weights to each criterion, allowing for flexibility in reflecting the relative importance of criteria in decision-making scenarios.

Sensitivity Analysis:

Conduct sensitivity analyses to understand the impact of changes in criteria weights on the final decision. This pacakge provides tools for exploring various scenarios and making informed decisions.

Result Interpretation:

The package provides intuitive result interpretation, presenting the ranked alternatives based on their closeness to the ideal solution. Detailed reports and visualizations aid in understanding the decision-making process.

Compatibility:

This pacakge is compatible with Python 3.x and integrates seamlessly into various data science and analytics workflows. It can be easily incorporated into Jupyter notebooks, scripts, or larger applications.

How to install this package:

>> pip install TOPSIS-Anirudh-102283008

In Command Prompt

>> topsis data.csv "1,1,2,1" "+,+,-,+" result.csv