102203525_TOPSIS

102203525_TOPSIS is a Python package that implements the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method, which is a multi-criteria decision analysis method. This package allows users to calculate TOPSIS scores and ranks for given datasets.

Installation

You can install the package using pip:

pip install 102203525_TOPSIS

Command-Line Usage

After installation, you can use the run-topsis command to perform the analysis.

Command Syntax

run-topsis <input_data_file> <weights> <impacts> <result_file_name>

• <input_data_file>: Path to the input data file (CSV or Excel).
• <weights>: Comma-separated list of weights for each criterion.
• <impacts>: Comma-separated list of impacts for each criterion (+ for beneficial, - for non-beneficial).
• <result_file_name>: Path to save the result file (CSV or Excel).

Sample Command

run-topsis data/input.xlsx "0.4,0.3,0.2,0.1" "+,+,-,+" result/output.xlsx

How It Works

1. Data Loading: The script reads the input data from the specified file.
2. Normalization: Each column is normalized to make the data comparable.
3. Weighting: The normalized data is weighted according to the provided weights.
4. Ideal Solutions: Ideal best and worst solutions are determined based on the impacts (+ or -).
5. Separation Measures: The distance of each alternative from the ideal best and worst solutions is calculated.
6. TOPSIS Score: The relative closeness to the ideal solution is computed.
7. Ranking: Alternatives are ranked based on their TOPSIS scores.

Example

Input Data (input.xlsx):

Running the Command:

run-topsis input.xlsx "0.4,0.3,0.2,0.1" "+,+,-,+" output.xlsx

Result Data (output.xlsx):

By following the above steps, you can easily perform TOPSIS analysis using the 102203525_TOPSIS package. For any issues or suggestions, feel free to open an issue on the GitHub repository.

The Link to this Python Package on PyPi