This is a topsis package of version 0.3
Project description
Topsis_Kunal_102053007
TOPSIS
Submitted By: Kunal Madan - 102053007.
Type: Package.
Title: TOPSIS method for multiple-criteria decision making (MCDM).
Version: 1.0.0.
Date: 2022-01-22.
Author: Kunal Madan.
Maintainer: Kunal Madan kmadan_bemba20@thapar.edu.
Description: Evaluation of alternatives based on multiple criteria using TOPSIS method..
What is TOPSIS?
Technique for **Order **Preference by **Similarity to **Ideal **Solution (TOPSIS) originated in the 1980s as a multi-criteria decision making method. TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution, and greatest distance from the negative-ideal solution.
How to install this package:
pip install Topsis-Kunal-102053007
In Command Prompt
topsis data.csv "1,1,1,1,1" "+,+,-,+,-" result.csv
Input file (data.csv)
The decision matrix should be constructed with each row representing a Model alternative, and each column representing a criterion like Accuracy, R2, Root Mean Squared Error, Correlation, and many more.
| Model | P1 | P2 | P3 | P4 | P5 |
|---|---|---|---|---|---|
| M1 | 0.66 | 0.44 | 4.9 | 32.9 | 9.73 |
| M2 | 0.65 | 0.42 | 5 | 44.5 | 12.64 |
| M3 | 0.61 | 0.37 | 3.3 | 41.1 | 11.35 |
| M4 | 0.62 | 0.38 | 6.5 | 64.1 | 17.9 |
| M5 | 0.83 | 0.69 | 6.4 | 34.4 | 10.58 |
| M6 | 0.88 | 0.77 | 6.7 | 34.8 | 10.79 |
| M7 | 0.63 | 0.4 | 4.5 | 39.1 | 11.16 |
| M8 | 0.8 | 0.64 | 4.4 | 45.7 | 12.89 |
Weights (weights) is not already normalised will be normalised later in the code.
Information of benefit positive(+) or negative(-) impact criteria should be provided in impacts.
Output file (out.csv)
| Model | P1 | P2 | P3 | P4 | P5 | Topsis Score | Rank |
|---|---|---|---|---|---|---|---|
| M1 | 0.66 | 0.44 | 4.9 | 32.9 | 9.73 | 0.21189353869415917 | 6 |
| M2 | 0.65 | 0.42 | 5 | 44.5 | 12.64 | 0.3271776939542866 | 5 |
| M3 | 0.61 | 0.37 | 3.3 | 41.1 | 11.35 | 0.15153299377397803 | 8 |
| M4 | 0.62 | 0.38 | 6.5 | 64.1 | 17.9 | 0.5850881941527206 | 1 |
| M5 | 0.83 | 0.69 | 6.4 | 34.4 | 10.58 | 0.49092824102735394 | 3 |
| M6 | 0.88 | 0.77 | 6.7 | 34.8 | 10.79 | 0.5427136027309007 | 2 |
| M7 | 0.63 | 0.4 | 4.5 | 39.1 | 11.16 | 0.2008035122309426 | 7 |
| M8 | 0.8 | 0.64 | 4.4 | 45.7 | 12.89 | 0.48154813555267983 | 4 |
The output file contains columns of input file along with two additional columns having Topsis_score and Rank
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