Topsis-Dishav-102217004 0.5

A Python package for implementing the TOPSIS decision-making method.

# TOPSIS - Dishav_Singla-102217004

A Python implementation of the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method, designed for decision-making in multi-criteria decision analysis (MCDA).

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Project Description

This project implements the TOPSIS technique, a popular method used in decision-making that evaluates multiple alternatives based on various criteria. The project is focused on applying TOPSIS to a given dataset with multiple alternatives and criteria. The objective is to rank and identify the best alternative by calculating the relative closeness of each alternative to the ideal solution.

Objective

• To apply TOPSIS on a sample dataset.
• To rank different alternatives based on defined criteria.
• To generate a ranking list of the alternatives for decision-making purposes.

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Features

• Data Preprocessing: The dataset is cleaned and normalized.
• TOPSIS Algorithm: Implementation of the TOPSIS method, including the calculation of:
  • Ideal and negative-ideal solutions.
  • Separation measures.
  • Relative closeness to the ideal solution.
• Ranking: Rank the alternatives based on the relative closeness.
• Visualizations: Plot results (optional, if applicable).

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Installation

Prerequisites

Ensure you have Python 3.x installed. You can download it from the official website:

• Python Official Website

Install Dependencies

Clone this repository and install the necessary dependencies using pip:

git clone https://github.com/DISHAVSINGLA/TOPSIS-Dishav_Singla-102217004.git
cd TOPSIS-Dishav_Singla-102217004
pip install -r requirements.txt

Install Library

pip install TOPSIS-DishavSingla-102217004