Topsis-Rohit-102203804 1.2.0

Implementation of TOPSIS for multi-criteria decision making

Topsis-Rohit-102203804

A Python package implementing the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method for multi-criteria decision making. This package helps compute rankings for alternatives based on their proximity to ideal best and worst solutions.

Installation

Install the package using pip:

pip install Topsis-Rohit-102203804

Install required dependencies:

pip install pandas numpy pyexcel

Features

• Compute TOPSIS scores and rankings for alternatives
• Support for custom weights and impacts for decision criteria
• Export results to CSV file
• Comprehensive input validation
• Both command-line and programmatic usage
• Support for CSV and Excel input files

Usage

Command Line Interface

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

Parameters:

1. InputDataFile: Path to input dataset (CSV/XLSX)
2. Weights: Comma-separated criterion weights (e.g., "1,2,3")
3. Impacts: Comma-separated criterion impacts ('+' for maximize, '-' for minimize)
4. ResultFileName: Output file path for results

Example:

topsis data.csv "1,1,1,1,1" "+,+,-,+,-" result.csv

Python Package Usage

from topsis_rohit_102203804.topsis import topsis

# Perform TOPSIS analysis
topsis("input.csv", [1,1,1,1,1], ['+','+','-','+','-'], "output.csv")

Input Data Format

File Requirements

• Must contain at least 3 columns
• First column: Names of alternatives
• Columns 2 onwards: Numeric values for criteria

Example Input CSV:

Alternative,Criterion1,Criterion2,Criterion3
A1,250,16,12
A2,200,18,11
A3,180,20,10

Output Format

The package generates a CSV file with the original data plus two additional columns:

• Topsis Score: Calculated similarity to ideal solution
• Rank: Final ranking of alternatives

Error Handling

The package validates:

• Number of command-line arguments
• File existence and readability
• Minimum column requirement (3 or more)
• Numeric values in criteria columns
• Matching counts of weights, impacts, and criteria
• Valid impact symbols (+ or -)
• Proper formatting of weights and impacts (comma-separated)

Prerequisites

• Python 3.6 or higher
• Dependencies:
  • pandas
  • numpy
  • pyexcel

License

MIT License

Author

Rohit (GitHub Profile)