topsis-3112 0.1.0

TOPSIS implementation for MCDM problems

TOPSIS-Atishay-102303112

Project-1 (UCS659) Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)

topsis-aj is a Python library designed to solve Multiple Criteria Decision Making (MCDM) problems. It ranks alternatives based on their distance from an ideal solution and a negative-ideal solution.

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👤 Author Information

• Name: Atishay Jain
• Roll No: 102303112
• Group: 3C14

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📦 Installation

Use the package manager pip to install the library:

pip install topsis-aj

Usage

Run the TOPSIS command using the following syntax:

topsis <inputFileName.csv> <weights> <impacts> <resultFileName.csv>

Example

topsis sample.csv "1,1,1,1" "+,-,+,+"

Help

To view the usage instructions:

topsis /h

Example Dataset sample.csv

Model	Storage space (in GB)	Camera (in MP)	Price (in $)	Looks (out of 5)
M1	16	12	250	5
M2	16	8	200	3
M3	32	16	300	4
M4	32	8	275	4
M5	16	16	225	2

Weights Vector

[0.25, 0.25, 0.25, 0.25]

Impacts Vector

[+, +, -, +]

Input command

topsis sample.csv "0.25,0.25,0.25,0.25" "+,+,-,+" result.csv

Output

TOPSIS RESULTS

Index	P-Score	Rank
1	0.534277	3
2	0.308368	5
3	0.691632	1
4	0.534737	2
5	0.401046	4

Notes

• The first column and header row are removed before processing.

• All columns from the second to last must contain numeric values only.

• The number of weights, impacts, and criteria columns must be equal.

• Impacts must be either + or -.

License

This project is licensed under the MIT License.