Topsis-Vansh-102303806 0.0.2

TOPSIS command-line tool

TOPSIS Algorithm Implementation

Program 1: Overview

TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is a multi-criteria decision-making (MCDM) technique used to rank alternatives based on their relative closeness to the ideal best and ideal worst solutions.

This project provides a complete command-line based Python implementation of the TOPSIS algorithm with proper validation and result generation.

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Features

• Accepts custom weights and impacts for each criterion
• Computes TOPSIS Score and Rank
• Works as a command-line program
• Generates results in a CSV output file
• Robust error handling and input validation
• Available as an installable PyPI package

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How TOPSIS Works (Brief)

1. Normalize the decision matrix
2. Apply weights to normalized values
3. Determine ideal best and ideal worst solutions
4. Compute separation measures
5. Calculate TOPSIS score
6. Rank alternatives based on score

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How to Use

Prerequisites

• Python 3.7 or higher
• Required libraries:
  • pandas
  • numpy

Install dependencies (if running from source):

pip install pandas numpy

Command-Line Usage

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

Parameters

1. InputDataFile: Path to the dataset file (CSV/XLSX). The first column lists alternatives, followed by numeric data for criteria.
2. Weights: Comma-separated values for criterion importance (e.g., "1,2,3").
3. Impacts: Comma-separated values (+ for maximize, - for minimize) indicating desired impact for each criterion (e.g., "+,-,+").
4. ResultFileName: Name of the output file where results will be saved.

Example Command

topsis sample_input.csv "1,1,1,1" "+,+,+,+" output.csv