topsis_harshit_102303276 0.1.0

Implementation of the TOPSIS Algorithm

TOPSIS-Harshit-102303276

A Python package to implement the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). This command-line tool takes a dataset of alternatives and criteria, applies weights and impacts, and calculates a ranking score for each alternative.

Installation

You can install this package via pip:

pip install topsis-harshit-102303276

Usage

The package can be used through the command line. It requires an input CSV or Excel file containing your data, a string of weights, a string of impacts, and the name of the output file.

Command Syntax

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

Arguments

1. InputDataFile: Path to the .csv or .xlsx file.

   • The file must contain 3 or more columns.
   • First column: Object/Model Name (e.g., M1, M2, M3). This column is not used in calculations but is preserved in the output.
   • Remaining columns: Numeric values representing the criteria for each object.

2. Weights: Comma-separated numbers indicating the importance of each criterion (e.g., "1,1,1,1").

3. Impacts: Comma-separated signs (+ or -) indicating the desired direction of the criterion.

   • +: Higher value is better (Profit).
   • -: Lower value is better (Cost).

4. ResultFileName: Name of the output CSV file where results will be saved.

Example

Let's assume we want to rank 5 different mobile phone models based on 4 criteria: Price, Storage, Camera, and Looks.

1. Input Data (data.csv)

Model	Price	Storage	Camera	Looks
M1	250	16	12	5
M2	200	16	8	3
M3	300	32	16	4
M4	275	32	8	4
M5	225	16	16	2

• Criteria Analysis:
• Price: Lower is better (- impact).
• Storage: Higher is better (+ impact).
• Camera: Higher is better (+ impact).
• Looks: Higher is better (+ impact).

2. Execution

Run the following command in your terminal:

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

• Weights: 1,1,1,1 (All criteria are equally important).
• Impacts: -,+,+,+ (Price is negative impact, others are positive).

3. Output Data (result.csv)

The tool generates a new file result.csv containing the original data with two additional columns: Topsis Score and Rank.

Model	Price	Storage	Camera	Looks	Topsis Score	Rank
M1	250	16	12	5	0.534277	3
M2	200	16	8	3	0.308368	5
M3	300	32	16	4	0.691632	1
M4	275	32	8	4	0.534737	2
M5	225	16	16	2	0.492650	4