A Python package for implementing the TOPSIS decision-making method.
Project description
# 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).
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.
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).
Installation
Prerequisites
Ensure you have Python 3.x installed. You can download it from the official website:
Install Dependencies
Clone this repository and install the necessary dependencies using pip:
git clone https://github.com/your-username/TOPSIS-Dishav_Singla-102217004.git
cd TOPSIS-Dishav_Singla-102217004
pip install -r requirements.txt
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