Topsis-Trishti-102313056 0.1.0

A Python package implementing TOPSIS for multi-criteria decision making

Topsis-Trishti-102313056

For: Project-1 (UCS654) Submitted by: Trishti Roll No: 102313056 Group: 3C33

Topsis-Trishti-10155792 is a Python library designed to solve Multiple Criteria Decision Making (MCDM) problems using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method.

The package helps users rank alternatives based on multiple quantitative criteria by calculating their closeness to the ideal best and ideal worst solutions. It is implemented as a command-line tool, making it easy to use for academic and real-world decision-making problems.

Installation

The package can be installed using the Python package manager pip.

pip install Topsis-Trishti-10155792

Usage

Provide the input CSV file name, followed by the weights vector and the impacts vector.

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

Alternatively, vectors can be passed without quotes:

topsis input.csv 1,1,1,1 +,+,-,+

Note: If the vectors contain spaces, they must be enclosed within double quotes " ".

To view help instructions, use:

topsis /h

Example

Input File: sample.csv

A CSV file containing data for different mobile handsets with multiple attributes.

Model	Storage (GB)	Camera (MP)	Price ($)	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:

[+, +, -, +]

Command

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

Output

        TOPSIS RESULTS
-----------------------------
   Topsis Score   Rank
1     0.534277      3
2     0.308368      5
3     0.691632      1
4     0.534737      2
5     0.401046      4

The output file contains the TOPSIS score and rank for each alternative.

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Important Notes

• The first column (identifiers) and the header row are ignored during computation.
• The CSV file must contain only numerical values (no categorical data).
• The number of weights and impacts must match the number of criteria.
• Impacts must be either + (benefit) or - (cost).

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