Evaluation of alternatives based on multiple criteria using TOPSIS method.
Project description
Topsis_102003592
TOPSIS - Multiple Criteria Decision Making
Submitted By: Bhavna Goyal - 102003592.
Type: Package.
Title: TOPSIS method for multiple-criteria decision making (MCDM).
Version: 0.3.
Date: 21-01-2023.
Author: Bhavna Goyal.
Maintainer: Bhavna Goyal bgoyal_be20@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_102003592
In Command Prompt
>> topsis data.csv "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.
| Attribute | Price or cost | Storage Space | Camera | Looks |
|---|---|---|---|---|
| Mobile 1 | 250$ | 16GB | 12MP | 5 |
| Mobile 2 | 200$ | 16GB | 8MP | 3 |
| Mobile 3 | 300$ | 32GB | 16MP | 4 |
| Mobile 4 | 275$ | 32GB | 8MP | 4 |
| Mobile 5 | 225$ | 16GB | 16MP | 2 |
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 (result.csv)
| Attribute | Price or cost | Storage Space | Camera | Looks | Topsis_score | Rank |
|---|---|---|---|---|---|---|
| Mobile 1 | 250$ | 16GB | 12MP | 5 | 0.4228 | 4 |
| Mobile 2 | 200$ | 16GB | 8MP | 3 | 0.4635 | 3 |
| Mobile 3 | 300$ | 32GB | 16MP | 4 | 0.5097 | 2 |
| Mobile 4 | 275$ | 32GB | 8MP | 4 | 0.3772 | 5 |
| Mobile 5 | 225$ | 16GB | 16MP | 2 | 0.6871 | 1 |
The output file contains columns of input file along with two additional columns having *Topsis_score* and *Rank*
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file Topsis_102003592-0.3.tar.gz.
File metadata
- Download URL: Topsis_102003592-0.3.tar.gz
- Upload date:
- Size: 3.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.7.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ec1b56e23d54d328f39bbfce4486556d256a7c7f9ae4004cd744ef1743315a6a
|
|
| MD5 |
bc68410724ea3d783fc7c4ba87eb4fe1
|
|
| BLAKE2b-256 |
b690954a9fbe3179c76f346767ec5d65bd0fe24c712703de611c7af02c7020d0
|
File details
Details for the file Topsis_102003592-0.3-py3-none-any.whl.
File metadata
- Download URL: Topsis_102003592-0.3-py3-none-any.whl
- Upload date:
- Size: 4.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.7.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
6237e89109555bb3b05b98628bfbaa629dd66593cbe58a4d4f5269b922f51c11
|
|
| MD5 |
2bf21823c78da4b485f1cb1576640f27
|
|
| BLAKE2b-256 |
70d60297bcc404f0575f301319e27100ee7972f58e3d00b61304a86b0e7646f9
|