Skip to main content

A Python package to get best alternative available using TOPSIS method.

Project description

TOPSIS-Gurleen-101903399

A python package which implements TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) which is a multi-criteria decision analysis method.

Steps involved in TOPSIS Algorithm:

1. Creating an evaluation matrix (m x n).
2. Normalization of the matrix so formed such that each metric for a given model lies between 0 and 1.
3. Creating a weighted normalized matrix i.e. multiplying the metrics with the weights of respective model.
4. Determining the ideal best and ideal worst alternatives for each criterion.
5. Calculating the euclidean distance between the target alternative and ideal best and idealworst alternatives.
6. Calculate the TOPSIS score i.e. similarity to the ideal worst alternative.
7. Rank the models on the basis of the TOPSIS score thus obtained.s

Usage

Running the following query on the command-line interface will help you to rank the models i.e. choose the best alternative available from a given set of models based on multiple, usually conflicting criteria.

TOPSIS-Gurleen-101903399 <data_file_name> <weights> <impacts> <result_file_name>
Example - TOPSIS-Gurleen-101903399 data.csv "1,1,1,2" "+,+,-,+" result.csv

Note - Make sure that you run the command in the folder you have stored your data files , else provide the complete path of the file.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

TOPSIS-Gurleen-101903399-1.0.3.tar.gz (4.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

TOPSIS_Gurleen_101903399-1.0.3-py3-none-any.whl (5.1 kB view details)

Uploaded Python 3

File details

Details for the file TOPSIS-Gurleen-101903399-1.0.3.tar.gz.

File metadata

  • Download URL: TOPSIS-Gurleen-101903399-1.0.3.tar.gz
  • Upload date:
  • Size: 4.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.25.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/3.8.1 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.3 CPython/3.6.9

File hashes

Hashes for TOPSIS-Gurleen-101903399-1.0.3.tar.gz
Algorithm Hash digest
SHA256 2995f5d2effdd940a9bbb92f274af79eabb82967d1912e0b5930491e98b67ebe
MD5 68dd6d54184050a0f86d0a9f8e876d8b
BLAKE2b-256 8c39f19686be0e9df2b59f9b93d2322ca8e2bfc3a74d42b52d9042c09f1fefd4

See more details on using hashes here.

File details

Details for the file TOPSIS_Gurleen_101903399-1.0.3-py3-none-any.whl.

File metadata

  • Download URL: TOPSIS_Gurleen_101903399-1.0.3-py3-none-any.whl
  • Upload date:
  • Size: 5.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.25.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/3.8.1 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.3 CPython/3.6.9

File hashes

Hashes for TOPSIS_Gurleen_101903399-1.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 bd6174861e12d887030a424779723a6e4fdf4b22d0335e2377df8b4e9caba9be
MD5 1d36724d5f43657bedfe2e44d9356379
BLAKE2b-256 dbc4d7a00b5d65087c4abf0bf60bc8d8bcd3228b7086367e88bba7e1ac29f410

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page