A Python package for TOPSIS multi-criteria decision-making.
Project description
TOPSIS Implementation in Python
This repository contains a Python implementation of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), a multi-criteria decision-making (MCDM) method. TOPSIS is used to rank and evaluate alternatives based on multiple criteria, considering both their closeness to an ideal solution and their distance from a nadir (worst-case) solution.
Features
- Accepts input data from a CSV file for analysis.
- Normalizes numerical data using vector normalization.
- Applies user-defined weights and impacts (
+for benefit criteria,-for cost criteria) to compute the weighted normalized decision matrix. - Calculates ideal and anti-ideal solutions and their respective distances for each alternative.
- Computes the TOPSIS score and assigns ranks to alternatives.
- Outputs results including TOPSIS scores and ranks in a CSV file.
Installation
Clone the repository and install the required Python libraries:
pip install pandas numpy scipy
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