Topsis-Khushi-102303610 1.0.0

A Python package for TOPSIS multi-criteria decision making method

TOPSIS — Khushi (102303610)

Topsis-Khushi-102303610 is a Python library for solving Multiple Criteria Decision Making (MCDM) problems using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).

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What is TOPSIS?

TOPSIS is a decision-making method used when you need to choose the best option from several alternatives based on multiple criteria.

Core Concept

The best alternative should have:

• The shortest distance from the Positive Ideal Solution (best possible values)
• The longest distance from the Negative Ideal Solution (worst possible values)

Simple Example

Imagine choosing a mutual fund based on:

• P1 (higher is better) ✓
• P2 (higher is better) ✓
• P3 (lower is better) ✗
• P4 (higher is better) ✓

TOPSIS calculates a score for each fund and ranks them to help you pick the best one!

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Features

• ✅ Simple command-line interface
• ✅ Handles any number of alternatives and criteria
• ✅ Automatic normalization of data
• ✅ Supports both beneficial (+) and non-beneficial (-) criteria
• ✅ Generates ranked output with TOPSIS scores
• ✅ Easy to install and use

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Installation

Install the package using pip:

pip install Topsis-Khushi-102303610

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Usage

Run TOPSIS from the command line:

topsis <InputFile.csv> <Weights> <Impacts> <OutputFile.csv>

Method 1: With Quotes (Recommended)

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

Method 2: Without Quotes

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

Important:
Method 2 does not allow spaces. Always use quotes if there are spaces in your input.

Get Help

topsis -h

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Input File Format

The input must be a CSV file with the following structure:

Requirements

• First column: Names or IDs of alternatives (text)
• Remaining columns: Numerical criteria values only
• First row: Column headers

Example: data.csv

Fund Name,P1,P2,P3,P4
M1,0.67,0.45,6.5,42.6
M2,0.6,0.36,3.6,53.3
M3,0.82,0.67,3.8,63.1
M4,0.6,0.36,3.5,69.2

Where:

• Fund Name = Name of the mutual fund
• P1, P2, P3, P4 = Different performance criteria to evaluate

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Example

Input File: data.csv

Fund Name,P1,P2,P3,P4
M1,0.67,0.45,6.5,42.6
M2,0.6,0.36,3.6,53.3
M3,0.82,0.67,3.8,63.1
M4,0.6,0.36,3.5,69.2

Command

topsis data.csv "0.25,0.25,0.25,0.25" "+,+,-,+" output.csv

Parameters Explained

Parameter	Value	Meaning
Weights	0.25,0.25,0.25,0.25	All criteria have equal importance (25% each)
Impacts	+,+,-,+	P1 ✓, P2 ✓, P3 ✗, P4 ✓

Impacts:

• + means higher is better (beneficial)
• - means lower is better (non-beneficial)

Output: output.csv

Fund Name,P1,P2,P3,P4,Topsis Score,Rank
M1,0.67,0.45,6.5,42.6,0.448532,3
M2,0.6,0.36,3.6,53.3,0.532891,2
M3,0.82,0.67,3.8,63.1,0.691876,1
M4,0.6,0.36,3.5,69.2,0.589247,2

Result: Fund M3 is ranked 1st (best choice) with the highest TOPSIS Score.

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Input Validation Rules

The package validates your input to ensure correctness:

Rule	Description
✓ File format	Must be a .csv file
✓ Minimum alternatives	At least 2 rows of data
✓ Minimum criteria	At least 2 criteria columns
✓ Numeric values	All criteria values must be numbers
✓ Matching counts	Number of weights = Number of impacts = Number of criteria
✓ Valid impacts	Only + or - allowed
✓ Positive weights	All weights must be > 0

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How TOPSIS Works (Algorithm)

1. Normalize the decision matrix
2. Calculate the weighted normalized matrix
3. Determine the Ideal Best (positive ideal solution)
4. Determine the Ideal Worst (negative ideal solution)
5. Calculate Euclidean distances from ideal best and worst
6. Compute TOPSIS performance score for each alternative
7. Rank alternatives (1 = best)

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Error Handling

Common errors and solutions:

Error	Cause	Solution
File not found	Wrong file path	Check the file name and path
Wrong number of parameters	Mismatch in counts	Ensure weights, impacts, and criteria match
Non-numeric values	Text in criteria columns	All criteria must be numbers (except first column)
Invalid impact	Wrong symbol used	Use only + or -
Invalid weights	Zero or negative weight	All weights must be positive numbers

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Package Information

Author: Khushi
Roll Number: 102303610
Institution: Thapar Institute of Engineering and Technology
Version: 1.0.0
License: MIT

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Keywords

TOPSIS, MCDM, Multi-Criteria Decision Making, Decision Analysis, Optimization, Python, Data Science, Operations Research

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For any issues or questions, please refer to the package documentation or contact the author.