Topsis-Shweta-2004

TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is a multi-criteria decision-making method. This package implements TOPSIS in Python — it takes a decision matrix CSV, weights, and impacts, then returns a ranked result.

Installation

pip install Topsis-Shweta-2004

Usage

In Python:

from Topsis_Shweta_2004.topsis import topsis

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

Via Command Line:

python -m Topsis_Shweta_2004.topsis input.csv "1,1,1,2" "+,+,-,+" output.csv

Parameters:

Input Format

First column = object/alternative name. Remaining columns = numeric criteria.

Output Format

Same as input with two additional columns: Topsis Score and Rank.

How TOPSIS Works

1. Normalize the decision matrix
2. Apply weights to each criterion
3. Find Ideal Best & Worst solutions
4. Calculate distance from ideal best and worst
5. Rank alternatives by closeness to ideal solution

Error Handling

• File not found → clear error message
• Mismatched weights/impacts/columns → ValueError
• Non-numeric values in criteria columns → ValueError

Requirements

• Python 3
• pandas
• numpy

License

(c) 2024 Shweta — MIT License