Skip to main content

A Python package to choose the best alternative from a finite set of decision alternatives.

Project description

#TOPSIS Package

TOPSIS stands for Technique for Oder Preference by Similarity to Ideal Solution. It is a method of compensatory aggregation that compares a set of alternatives by identifying weights for each criterion, normalising scores for each criterion and calculating the geometric distance between each alternative and the ideal alternative, which is the best score in each criterion. An assumption of TOPSIS is that the criteria are monotonically increasing or decreasing. In this Python package Vector Normalization has been implemented.

This package has been created based on Project 1 of course UCS633. Anurag Aggarwal COE-4 101703088

#In Command Prompt

topsis data.csv "1,1,1,1" "+,+,-,+"

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-Anurag-1.0.0.tar.gz (3.1 kB view details)

Uploaded Source

Built Distribution

topsis_Anurag-1.0.0-py3-none-any.whl (2.8 kB view details)

Uploaded Python 3

File details

Details for the file topsis-Anurag-1.0.0.tar.gz.

File metadata

  • Download URL: topsis-Anurag-1.0.0.tar.gz
  • Upload date:
  • Size: 3.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.4.2 requests/2.22.0 setuptools/39.1.0 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.6.5

File hashes

Hashes for topsis-Anurag-1.0.0.tar.gz
Algorithm Hash digest
SHA256 870da6b06d7f1973075c8a4616827767d731011e2f77d1263d5cdbe8c33ad08d
MD5 76d82ff06cecce104753967d41e87cd2
BLAKE2b-256 7c9208de7e0fd6b32fe43ac203a89f86a6c84899cfb77d875389506dd92b2361

See more details on using hashes here.

File details

Details for the file topsis_Anurag-1.0.0-py3-none-any.whl.

File metadata

  • Download URL: topsis_Anurag-1.0.0-py3-none-any.whl
  • Upload date:
  • Size: 2.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.4.2 requests/2.22.0 setuptools/39.1.0 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.6.5

File hashes

Hashes for topsis_Anurag-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 74b804258fd4a767d1a87c061f1ab8e3f7ada024aadec495429fa7168a52912e
MD5 2698a894a456f39088e5ff9a694cfdb2
BLAKE2b-256 bed7a81f6d852d5dab62b6b6cdf531aee0623af1c8adff0c5e936d1c077f2368

See more details on using hashes here.

Supported by

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