TOPSIS Implementation in
This repository contains a Python implementation of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). TOPSIS is a multi-criteria decision-making method that helps in ranking a set of alternatives based on their proximity to the ideal solution.
Usage
To use this TOPSIS implementation, follow these steps:
1.Ensure you have Python installed on your system.
2.Clone this repository to your local machine:
git clone https://github.com/cheshtabiala/Assignment-Topsis
3.Navigate to the project directory:
cd your-repo
4.Run the TOPSIS script with the required command-line arguments:
python topsis.py <InputDataFile> <Weights> <Impacts> <ResultFileName>
Example:python topsis.py input_data.csv "1,1,1,2" "+,+,-,+" result.csv
5.The TOPSIS analysis will be performed, and the result will be saved to the specified CSV file.
Command-line Arguments:
<InputDataFile>: Path to the input CSV file containing the decision matrix.
<Weights>: Comma-separated weights for each criterion.
<Impacts>: Comma-separated impact signs for each criterion (use '+' for beneficial criteria and '-' for non-beneficial criteria).
<ResultFileName>: Desired name for the output CSV result file.
Example:python topsis.py input_data.csv "1,1,1,2" "+,+,-,+" result.csv
Requirements:
Python 3.x
pandas
numpy
Author:
Cheshta Biala
License:
This project is licensed under the MIT License - see the LICENSE.md file for details.
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"description": "TOPSIS Implementation in \n\nThis repository contains a Python implementation of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). TOPSIS is a multi-criteria decision-making method that helps in ranking a set of alternatives based on their proximity to the ideal solution.\n\nUsage\nTo use this TOPSIS implementation, follow these steps:\n\n1.Ensure you have Python installed on your system.\n\n2.Clone this repository to your local machine:\n\n git clone https://github.com/cheshtabiala/Assignment-Topsis\n\n3.Navigate to the project directory:\n\n cd your-repo\n \n4.Run the TOPSIS script with the required command-line arguments:\n\n\n\n python topsis.py <InputDataFile> <Weights> <Impacts> <ResultFileName>\n Example:python topsis.py input_data.csv \"1,1,1,2\" \"+,+,-,+\" result.csv\n\n5.The TOPSIS analysis will be performed, and the result will be saved to the specified CSV file.\n\nCommand-line Arguments:\n\n<InputDataFile>: Path to the input CSV file containing the decision matrix.\n\n<Weights>: Comma-separated weights for each criterion.\n\n<Impacts>: Comma-separated impact signs for each criterion (use '+' for beneficial criteria and '-' for non-beneficial criteria).\n\n<ResultFileName>: Desired name for the output CSV result file.\n\n Example:python topsis.py input_data.csv \"1,1,1,2\" \"+,+,-,+\" result.csv\n\nRequirements:\nPython 3.x\npandas\nnumpy\n\nAuthor:\nCheshta Biala\n\nLicense:\nThis project is licensed under the MIT License - see the LICENSE.md file for details.\n",
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