topsis-prashant-102353011 1.0.0

TOPSIS implementation in Python

TOPSIS Implementation in Python

📌 Project Overview

This project implements the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method using Python.

TOPSIS is a Multi-Criteria Decision Making (MCDM) technique used to rank alternatives based on their distance from the ideal best and ideal worst solutions.

This project provides:

• A command-line TOPSIS program
• Support for CSV and Excel (.xlsx) files
• Robust input validation and error handling
• Ready-to-package structure for PyPI
• Scope for extension into a web service

📊 Input File Format

The input file must be a CSV or Excel (.xlsx) file with the following format:

Fund Name P1 P2 P3 P4 P5 M1 0.84 0.71 6.7 42.1 12.59 M2 0.91 0.83 7.0 31.7 10.11

Rules

• The first column must contain alternative names
• From the second column onward, all values must be numeric
• A minimum of 3 columns is required (1 alternative column + at least 2 criteria)

⚙️ Installation Requirements

Install the required Python libraries:

pip install pandas numpy openpyxl

🚀 How to Run the Program

Command Line Usage

python topsis.py <InputFile> <Weights> <Impacts> <OutputFile>

Example

python topsis.py data.xlsx "1,1,1,1,1" "+,+,-,+,+" result.xlsx

📥 Parameters Explanation

Parameter Description InputFile Input data file (.csv or .xlsx) Weights Comma-separated numeric values (e.g., "1,1,1,1,1") Impacts Comma-separated impacts (+ for benefit, - for cost) OutputFile Output file (.csv or .xlsx)

📈 Output File

The output file contains two additional columns:

• Topsis Score
• Rank

Higher TOPSIS Score indicates a better alternative.

🛑 Error Handling & Validations

The program validates:

• Incorrect number of arguments
• File not found
• Less than 3 columns in input file
• Non-numeric values in criteria columns
• Mismatch between number of weights, impacts, and criteria
• Invalid impacts (must be + or -)
• Unsupported file formats

Clear error messages are displayed for each case.

🧠 TOPSIS Methodology (Brief)

1. Normalize the decision matrix\
2. Apply weights to the normalized matrix\
3. Determine ideal best and ideal worst\
4. Calculate distances from ideal solutions\
5. Compute TOPSIS score\
6. Rank alternatives

📦 Packaging & PyPI

This project can be packaged using setuptools and uploaded to PyPI using the naming convention:

Topsis-FirstName-RollNumber

Example

Topsis-Prashant-102353011

Once uploaded, users can install it via:

pip install Topsis-Prashant-102353011

🌐 Web Service (Extension)

This project can be extended into a Flask-based web service where:

• Users upload the input file\
• Provide weights, impacts, and email ID\
• Receive the result file via email

This allows the TOPSIS tool to be used as a lightweight online service.

👤 Author

Prashant Gagneja
TOPSIS Assignment -- Python & PyPI

📜 License

This project is licensed for academic and educational use only.

⭐ Contributions

Feel free to fork this repository, raise issues, and submit pull requests to improve functionality or add features such as:

• GUI or Web UI\
• Additional MCDM methods\
• Visualization of rankings

📬 Contact

For queries or enhancements, please contact:
Prashant Gagneja