Topsis-Ishita-102317254 1.0.2

TOPSIS implementation for Multi-Criteria Decision Making

Topsis-Ishita-102317254

A Python package that implements the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for Multi-Criteria Decision Making (MCDM) problems.

This package works as:

• A Command Line Interface (CLI) tool
• A reusable Python module

It generates an output CSV file containing the TOPSIS Score and Rank for each alternative.

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Installation

Install the package directly from PyPI:

pip install Topsis-Ishita-102317254

Quick Start

Command Syntax

After installation, use the topsis command from the terminal:

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

Parameters

The command accepts exactly 4 parameters:

Parameter	Format	Example	Description
Input file	Path string	"data.csv"	Path to your CSV file
Weights	Comma-separated string	"1,1,1,1,2"	Weight for each criterion
Impacts	Comma-separated string	"+,+,+,-,+"	+ for benefit, - for cost
Output file	Path string	"result.csv"	Where to save results

Example Execution

Grab an input csv or excel file strictly adheres to the following structure:

1. The file must have at least 3 columns- Candidate Identifier column followed by min. 2 criteria.
2. The first column must contain the names/IDs of the alternatives.
3. Criteria columns must contain only numeric values.

A sample dataset file (data.csv) is shown below:

Fund Name	P1	P2	P3	P4	P5
M1	0.94	0.88	6.5	38.8	11.78
M2	0.69	0.48	4.4	59.8	16.34
M3	0.62	0.38	3.8	41.3	11.53
M4	0.63	0.40	6.1	50.5	14.41
M5	0.78	0.61	5.2	67.8	18.60
M6	0.61	0.37	5.6	34.6	10.30
M7	0.69	0.48	4.8	57.8	15.94
M8	0.75	0.56	6.1	62.4	17.45

Run the following command through the terminal.

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

The output file (result.csv) generated will look like this:

Fund Name	P1	P2	P3	P4	P5	Topsis Score	Rank
M1	0.94	0.88	6.5	38.8	11.78	0.5840384375	2
M2	0.69	0.48	4.4	59.8	16.34	0.4489649725	4
M3	0.62	0.38	3.8	41.3	11.53	0.2617528226	8
M4	0.63	0.40	6.1	50.5	14.41	0.3974983163	6
M5	0.78	0.61	5.2	67.8	18.60	0.5917499869	1
M6	0.61	0.37	5.6	34.6	10.30	0.3159064238	7
M7	0.69	0.48	4.8	57.8	15.94	0.4461587287	5
M8	0.75	0.56	6.1	62.4	17.45	0.5714234615	3

Sample input file is available in the sample_data/ folder. Sample output file is available in the results/ folder.

Validations Implemented

• Input file existence check
• Minimum column requirement
• Numeric validation for criteria columns
• Matching count of weights and impacts
• Impact validation (+ or - only)
• Proper command-line argument count

License

This project is licensed under the MIT License. See the license text at: https://opensource.org/licenses/MIT

Author

Ishita Goyal
Penultimate-Year Student, BE-CSE
Thapar Institute of Engineering and Technology, Patiala

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