Topsis-Aartha-102302941 1.0.7

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TOPSIS-Aartha-102302941

A robust Python command-line utility to implement the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method.
This tool helps in multi-criteria decision-making by ranking alternatives based on their geometric distance from the ideal best and worst solutions.

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🛠️ Installation

Install the package directly from PyPI:

pip install Topsis-Aartha-102302941

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💻 Usage

Run the package using:

topsis <InputDataFile> <Weights> <Impacts> <ResultFileName>

Parameters

• InputDataFile → Path to the .csv file
• Weights → Comma-separated numeric values
  Example: "1,1,1,2"
• Impacts → Comma-separated signs (+ or -)
  Example: "+,+,-,+"
• ResultFileName → Output .csv file name

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📌 Requirements

• Input file must contain at least 3 columns
• Column 1 → Alternative names/IDs
• Column 2 onward → Numeric criteria only

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📊 Example

Input (data.csv)

Alternative	P1	P2	P3	P4
M1	250	16	12	5
M2	200	16	8	3
M3	300	32	16	4

Command

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

Output (result.csv)

The output file will include:

• Original data
• Topsis Score
• Rank (1 = Best)

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🧠 Workflow

1. Validation

   • Checks column count, weights, impacts, and numeric data

2. Preprocessing

   • Converts values to numeric
   • Handles missing values using mean imputation

3. Normalization

   • Uses Euclidean normalization

4. Ideal Solutions

   • Determines:
     • V⁺ (Best)
     • V⁻ (Worst)

5. Closeness Score

   • Computes distance from ideal best and worst

6. Ranking

   • Assigns rank based on closeness score

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👤 Author

Aartha Singh

• 🌐 Portfolio: https://myportfolio-phi-one-88.vercel.app/
• 🐈 GitHub: https://github.com/WorkaholicCat

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📜 License

Distributed under the MIT License.
See LICENSE for more information.

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