Topsis-Kalpesh-102317087 1.0.6

TOPSIS implementation as a Python package

TOPSIS Implementation

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Overview

This Python package provides a clear and practical implementation of the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method for Multi-Criteria Decision Making (MCDM).

Using this package, users can rank multiple alternatives based on several numerical criteria by assigning weights and impacts (benefit or cost) to each criterion. The package is designed as a command-line tool and works directly with CSV files.

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Project Information

Field	Details
Course	Project-1
Author	Kalpesh Paliwal
Roll No	102317087
Group	3Q14

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Features

• Easy-to-use command-line interface
• Supports customizable weights and impacts
• Handles benefit (+) and cost (-) criteria
• Accepts CSV input and produces CSV output
• Automatically computes TOPSIS score and rank

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Installation

Use the Python package manager pip to install the package:

pip install Topsis-Kalpesh-102317087

topsis <input_file.csv> <weights> <impacts>

Arguments

Argument	Description
<input_file.csv>	Path to CSV file. First column must contain alternative names. Remaining columns must contain numerical criteria values.
<weights>	Comma-separated weights for each criterion (example: 0.2,0.2,0.2,0.2,0.2).
<impacts>	Comma-separated impacts for each criterion (+ for benefit, - for cost).

Example

The following dataset evaluates different investment funds based on five parameters.

Fund	P1	P2	P3	P4	P5
M1	0.74	0.55	3.1	64.7	17.27
M2	0.66	0.44	4.3	60.0	16.35
M3	0.62	0.38	3.9	46.1	12.75
M4	0.83	0.69	4.9	33.0	9.86
M5	0.75	0.56	5.6	40.8	11.93
M6	0.87	0.76	6.6	38.8	11.76
M7	0.88	0.77	6.5	36.5	11.16
M8	0.78	0.61	6.7	35.9	11.00

Weights and Impacts

Weights

0.2,0.2,0.2,0.2,0.2

Impacts

+,+,+,-,-

Execution Command

topsis data.csv "0.2,0.2,0.2,0.2,0.2" "+,+,+,-,-"

Output

The output file (output.csv) contains the original data along with two additional columns.

Fund	P1	P2	P3	P4	P5	Topsis Score	Rank
M1	…	…	…	…	…	0.5123	6
M2	…	…	…	…	…	0.4786	8
M3	…	…	…	…	…	0.5639	5
M4	…	…	…	…	…	0.7214	1
M5	…	…	…	…	…	0.6042	4
M6	…	…	…	…	…	0.6897	2
M7	…	…	…	…	…	0.6588	3
M8	…	…	…	…	…	0.4951	7

Output Columns

Column	Meaning
Topsis Score	Calculated TOPSIS performance score
Rank	Rank based on TOPSIS score (1 = best)

Input File Requirements

• Input file must be a valid CSV
• First column must contain alternative names
• All remaining columns must contain numerical values
• No categorical or missing values allowed

Error Handling

The package validates inputs and raises errors for:

• Mismatch between the number of criteria and weights
• Mismatch between the number of criteria and impacts
• Invalid impact values (only + or - allowed)
• Incorrect CSV structure

License

This project is licensed under the MIT License.
See the LICENSE file for details.

Contact

For questions or feedback, please contact: Kalpesh Paliwal 📧 [e-mail]