It evaluates alternatives based on multiple criteria using TOPSIS method
Project description
TOPSIS
Author: Aarushi Abrol.
Type: Package.
Title: TOPSIS method for multiple-criteria decision making (MCDM).
Version: 1.1.0
Date: 2022-1-22
Maintainer: Aarushi Abrol aabrol_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
In Command Prompt
>> topsis data.csv "1,1,1,1" "+,+,-,+" result.csv
License
© 2022 Aarushi Abrol
This repository is licensed under the MIT license. See LICENSE for 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-102003527-1.1.0.tar.gz.
File metadata
- Download URL: topsis-102003527-1.1.0.tar.gz
- Upload date:
- Size: 4.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
168fa255049663dfd7dbb323613eb5d21ae4d1e6530234615480a3b767b0afb9
|
|
| MD5 |
cbda934401fd89db65a9f20d4cdc5b10
|
|
| BLAKE2b-256 |
6790d126f77f97e8ecc7f186a367f8400922b9831b345b0e6042628b36b81ae7
|
File details
Details for the file topsis_102003527-1.1.0-py3-none-any.whl.
File metadata
- Download URL: topsis_102003527-1.1.0-py3-none-any.whl
- Upload date:
- Size: 4.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
7257f3cb54a0381f5cbef1dd0bac0dc7d77cede9323cc56a949b7140a7273d92
|
|
| MD5 |
acab20ddea8a342859fa7ae897a8e984
|
|
| BLAKE2b-256 |
9fd256e1678df14cfebca50d6c3c73e8e11a5bff0932d2c8ef18c0c30992011e
|
