Topsis-Rehnoor-102317137 1.0.0

A Python package for TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) - Multi-Criteria Decision Making

🎯 TOPSIS

Technique for Order Preference by Similarity to Ideal Solution

A powerful multi-criteria decision-making (MCDM) technique used to rank alternatives based on their distance from an ideal best and an ideal worst solution.

📦 Installation • 🚀 Quick Start • 📖 Documentation • 👤 Author

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💡 About

This Python package provides a clean, efficient, and command-line friendly implementation of TOPSIS, designed as part of an academic assignment and packaged professionally for real-world usage via PyPI.

✨ Key Features

Feature	Description
✅ Standard Compliant	Fully compliant with standard TOPSIS methodology
🖥️ CLI Support	Easy-to-use command-line interface
🛡️ Robust Validation	Comprehensive input validation and error handling
⚖️ Customizable	Supports customizable weights and impacts
📊 Ranked Output	Outputs ranked results with TOPSIS score
🪶 Lightweight	Minimal dependencies, easy installation via pip

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📦 Installation

Install directly from PyPI using pip:

pip install Topsis-Rehnoor-102317137

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🖥️ Usage

Run the package from the command line:

python -m topsis <input_file.csv> "<weights>" "<impacts>" <output_file.csv>

🔹 Example

python -m topsis data.csv "1,1,1,2" "+,+,-,+" result.csv

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📂 Input File Format

⚠️ Requirements:

• ✔️ Input file must be a CSV file
• ✔️ Must contain at least 3 criteria columns
• ✔️ First column → Alternative names (non-numeric)
• ✔️ Remaining columns → Numeric criteria values only

📋 Sample Input (data.csv)

Model	Cost	Performance	Maintenance	Mileage
M1	250	7.5	5	18
M2	300	8.0	6	20
M3	200	6.5	4	15

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📤 Output File

The output CSV file contains:

• 📌 All original columns
• 📊 Topsis Score
• 🏆 Rank (Rank 1 = Best Alternative)

📋 Sample Output

Model	Cost	Performance	Maintenance	Mileage	Topsis Score	Rank
M2	300	8.0	6	20	0.72	🥇 1
M1	250	7.5	5	18	0.58	🥈 2
M3	200	6.5	4	15	0.31	🥉 3

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🔬 Behind the Scenes (TOPSIS Steps)

┌─────────────────────────────────────────────────────────────┐
│                    TOPSIS Algorithm                          │
├─────────────────────────────────────────────────────────────┤
│  1️⃣  Normalize the decision matrix                          │
│  2️⃣  Apply user-defined weights                             │
│  3️⃣  Determine ideal best and worst solutions               │
│  4️⃣  Calculate Euclidean distances (S⁺ and S⁻)              │
│  5️⃣  Compute TOPSIS performance score                       │
│  6️⃣  Rank alternatives based on scores                      │
└─────────────────────────────────────────────────────────────┘

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🛠️ Technologies Used

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👤 Author

Rehnoor Aulakh

Computer Science Student

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📄 License

This project is licensed under the MIT License.

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