Project Description

• for: Assignment-1(UCS654)
• Submitted by: Himanshu Bansal
• Roll no: 102103568
• Group: 3COE20

TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution)

This Python script implements the TOPSIS method for multi-criteria decision-making. It takes a CSV file containing a decision matrix, weights, and impacts as input, and produces a ranked result based on the TOPSIS score.

Installation

pip install Topsis-Himanshu-102103568

Usage

from Topsis_Himanshu_102103568.topsis import topsis 
inputFile="sample.csv"
weights="1,1,1,1"
impacts="-,+,+,+"
resultFile="result.csv" 
topsis(inputFile, weights, impacts, resultFile)

OR

You can use this package via command line as:

python -m Topsis_Himanshu_102103568.topsis [InputDataFile as .csv] [Weights as a string] [Impacts as a string] [ResultFileName as .csv]

• InputDataFile: Path to the CSV file containing the input data.
• Weights: Comma-separated weights for each criterion.
• Impacts: Comma-separated impact direction for each criterion (+ for maximization, - for minimization).
• ResultFileName: Name of the file to save the TOPSIS results.

Requirements

• Python 3
• pandas
• numpy

Input File Format

The input data should be in a CSV format with the following structure:

Output

The script generates a CSV file containing the TOPSIS score and rank for each object:

Error Handling

• If the input file is not found, an error message will be displayed.
• If the number of weights, impacts, or columns in the decision matrix is incorrect, a ValueError will be raised.
• If the columns from the 2nd to the last do not contain numeric values, a ValueError will be raised.
• Any unexpected errors during the execution will be displayed.

LICENSE

(c) 2024 Himanshu Bansal

This project is licensed under the MIT License.