TOPSIS method for multiple-criteria decision making (MCDM).
Project description
TOPSIS Submitted By: Nidhi Bhasker
Type: Package.
Title: TOPSIS method for multiple-criteria decision making (MCDM).
Version: 1.0.0.
Author: Nidhi Bhasker.
Maintainer: Nidhi Bhasker nidhibhasker001@gmail.com.
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-nidhi In Command Prompt python topsis data.csv "1,1,1,1,1" "+,-,+,-,+" result.csv Input file (data.csv)
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)
The output file contains columns of input file along with two additional columns having Topsis_score and Rank
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-Nidhi-101916100-1.0.0.tar.gz.
File metadata
- Download URL: Topsis-Nidhi-101916100-1.0.0.tar.gz
- Upload date:
- Size: 3.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a25c7d86309468e7928289d0752c8c992f85969d6ec9c1c40eaf5cab6c4d18e8
|
|
| MD5 |
db201310c03857c32cd4b9e8738fedd1
|
|
| BLAKE2b-256 |
26a72c33e2d6f2566ed4bcf0ed57ea73018dd62bc62b59dbb40303f47e2bc3a7
|
File details
Details for the file Topsis_Nidhi_101916100-1.0.0-py3-none-any.whl.
File metadata
- Download URL: Topsis_Nidhi_101916100-1.0.0-py3-none-any.whl
- Upload date:
- Size: 3.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8e5bf54425e568289942b0238df54b04e64828eb5537f1b7a3b13057f13875a9
|
|
| MD5 |
c4ec9871ba9511c27800c3a32af62266
|
|
| BLAKE2b-256 |
567f0ea7eb47514d2c50824e9896bee49a5130c21d74cc3d3db5b0062949e281
|
