A Python package to implement the TOPSIS method for decision making.
Project description
TOPSIS Akash Package
Overview
The TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is a multi-criteria decision-making tool. This Python package allows you to implement the TOPSIS method for ranking and selecting alternatives based on multiple criteria.
How to Use
Run the program through command line as: Usages: python <program.py> Example: python 101556.py 101556-data.csv “1,1,1,2” “+,+,-,+” 101556-result.csv
Features
- Input data validation
- Weighted normalization of the decision matrix
- Calculation of ideal best and worst solutions
- Ranking alternatives based on their similarity to the ideal solution
- Supports command-line execution
Installation
Install the package using pip:
pip install topsis-akash
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-Akash-0.0.1.tar.gz.
File metadata
- Download URL: topsis-Akash-0.0.1.tar.gz
- Upload date:
- Size: 3.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.12.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
62cb6ca6fdaee1984df9ecafc1bfb53827ffea9de70eac844b998e3760b901a8
|
|
| MD5 |
c956c9bbaea8f02b5b703e50f2c59662
|
|
| BLAKE2b-256 |
9d899850f16937f7e8735a5333c0eebf3bc1e6774f2f26746273cd28a16c9c29
|
File details
Details for the file topsis_Akash-0.0.1-py3-none-any.whl.
File metadata
- Download URL: topsis_Akash-0.0.1-py3-none-any.whl
- Upload date:
- Size: 3.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.12.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
99550109a5723cc206061fe4e6dfe8e24d104487c5387cb44eaf3778887e5885
|
|
| MD5 |
35b5872bfec4dc76e093acebe829bb59
|
|
| BLAKE2b-256 |
c3085c00afdc8e2dcddfb6bc6e115f7b4d2fff5fc7e1e8da00305b4c7b3c2da9
|
