Skip to main content

TOPSIS implementation for decision making

Project description

topsis-hardik-102303494

Project Description

topsis-hardik-102303494 is a Python library for solving Multiple Criteria Decision Making (MCDM) problems using the
Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).

This project has been developed as part of Project-1 (UCS654)
and demonstrates how TOPSIS can be implemented as a command-line Python package and distributed via PyPI.


Student Details

  • Name: Hardik
  • Roll Number: 102303494
  • Course: UCS654
  • Project: Project-1 (TOPSIS)

Installation

Install the package using pip:

pip install topsis-hardik-102303494

TOPSIS CLI Usage

Command Format

topsis <input_file.csv> <weights> <impacts> <output_file.csv>

Parameters

  • input_file.csv: CSV file with dataset (first column: names, remaining: numeric criteria)
  • weights: Comma-separated numeric weights (use quotes if needed)
  • impacts: Comma-separated impacts (+ for benefit, - for cost)
  • output_file.csv: CSV file for results

Example

Input (sample.csv)

Model Storage (GB) Camera (MP) Price ($) Looks
M1 16 12 250 5
M2 16 8 200 3
M3 32 16 300 4
M4 32 8 275 4
M5 16 16 225 2

Command

topsis sample.csv "0.25,0.25,0.25,0.25" "+,+,-,+" output.csv

Output

Model Topsis Score Rank
M1 0.534277 3
M2 0.308368 5
M3 0.691632 1
M4 0.534737 2
M5 0.401046 4

Rank 1 = Best Alternative

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_hardik_102303494-0.1.1.tar.gz (3.1 kB view details)

Uploaded Source

Built Distribution

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

topsis_hardik_102303494-0.1.1-py3-none-any.whl (3.7 kB view details)

Uploaded Python 3

File details

Details for the file topsis_hardik_102303494-0.1.1.tar.gz.

File metadata

  • Download URL: topsis_hardik_102303494-0.1.1.tar.gz
  • Upload date:
  • Size: 3.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.3

File hashes

Hashes for topsis_hardik_102303494-0.1.1.tar.gz
Algorithm Hash digest
SHA256 6a86cc01ba21bc067d3b9e000b7cdd81d3370fb972d66c9728cb01bdc8f7a8ca
MD5 1899c64c190d2527a20667f3fdca2c5c
BLAKE2b-256 cba5890bf088a36661878cfb2adfb7c4882ad21a56f0acf5dd2940f141b5a759

See more details on using hashes here.

File details

Details for the file topsis_hardik_102303494-0.1.1-py3-none-any.whl.

File metadata

File hashes

Hashes for topsis_hardik_102303494-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 0da6241fd9fab1b4e15a203b6f1884c8971e24e865132d2f6033f44f699e62ec
MD5 10205468991e9f9501dcfd5526fb3225
BLAKE2b-256 a2057b75fb303b953b7817dbeb00eba0558224b8622db04e3072ea3875a044a2

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