# Topsis-Anshul
# TOPSIS Implementation
This repository contains a Python implementation of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). TOPSIS is a powerful multi-criteria decision-making method that assists in ranking a set of alternatives based on their proximity to the ideal solution.
## Table of Contents
1. [Introduction](#introduction)
2. [Usage](#usage)
3. [Command-line Arguments](#command-line-arguments)
6. [Requirements](#requirements)
## Introduction
The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a well-established method for decision-making. This Python implementation allows you to easily apply TOPSIS to your decision matrix and obtain a ranked list of alternatives.
### Key Concepts:
- Decision Matrix: Represents alternatives and criteria.
- Weights: Assign importance to criteria.
- Impacts: Indicate whether higher or lower values are favorable.
- Normalization: Ensures all criteria are on a similar scale.
- Ideal and Worst Solutions: Represent best and worst possible outcomes.
- Similarity and Dissimilarity Measures: Calculate proximity to ideal and dissimilarity to worst.
- TOPSIS Score: Combines similarity and dissimilarity measures.
- Ranking: Alternatives are ranked based on TOPSIS scores.
## Usage
1. Ensure you have Python installed on your system.
2. Clone this repository to your local machine:
bash
git clone https://github.com/anshulmahajan14/Topsis-Anshul
3. Navigate to the project directory:
bash
git clone https://github.com/anshulmahajan14/Topsis-Anshul
4. Run the TOPSIS script with the required command-line arguments:
python 102217060.py 102217060-data.csv "1,1,1,2" "+,+,-,+" result.csv
5. The TOPSIS analysis will be performed, and the result will be saved to the specified CSV file.
Raw data
{
"_id": null,
"home_page": null,
"name": "Topsis-Anshul-102217060",
"maintainer": null,
"docs_url": null,
"requires_python": null,
"maintainer_email": null,
"keywords": "Topsis, Topsis-Anshul-102217060, Anshul, Topsis-Anshul, 102217060",
"author": "Anshul",
"author_email": "amahajan2_be22@thapar.edu",
"download_url": "https://files.pythonhosted.org/packages/a7/af/972f712252112777cf29e957d7f245992c54726ef9983fcfa34bf81b2a9a/Topsis-Anshul-102217060-1.0.3.tar.gz",
"platform": null,
"description": "# Topsis-Anshul\r\n# TOPSIS Implementation\r\n\r\nThis repository contains a Python implementation of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). TOPSIS is a powerful multi-criteria decision-making method that assists in ranking a set of alternatives based on their proximity to the ideal solution.\r\n\r\n## Table of Contents\r\n\r\n1. [Introduction](#introduction)\r\n2. [Usage](#usage)\r\n3. [Command-line Arguments](#command-line-arguments)\r\n6. [Requirements](#requirements)\r\n\r\n## Introduction\r\n\r\nThe Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a well-established method for decision-making. This Python implementation allows you to easily apply TOPSIS to your decision matrix and obtain a ranked list of alternatives.\r\n\r\n### Key Concepts:\r\n\r\n- Decision Matrix: Represents alternatives and criteria.\r\n- Weights: Assign importance to criteria.\r\n- Impacts: Indicate whether higher or lower values are favorable.\r\n- Normalization: Ensures all criteria are on a similar scale.\r\n- Ideal and Worst Solutions: Represent best and worst possible outcomes.\r\n- Similarity and Dissimilarity Measures: Calculate proximity to ideal and dissimilarity to worst.\r\n- TOPSIS Score: Combines similarity and dissimilarity measures.\r\n- Ranking: Alternatives are ranked based on TOPSIS scores.\r\n\r\n## Usage\r\n\r\n1. Ensure you have Python installed on your system.\r\n\r\n2. Clone this repository to your local machine:\r\n\r\n bash\r\n git clone https://github.com/anshulmahajan14/Topsis-Anshul\r\n\r\n3. Navigate to the project directory:\r\n\r\n bash\r\n git clone https://github.com/anshulmahajan14/Topsis-Anshul\r\n\r\n \r\n4. Run the TOPSIS script with the required command-line arguments:\r\n\r\n \r\n python 102217060.py 102217060-data.csv \"1,1,1,2\" \"+,+,-,+\" result.csv\r\n\r\n\r\n\r\n5. The TOPSIS analysis will be performed, and the result will be saved to the specified\u00a0CSV\u00a0file.\r\n",
"bugtrack_url": null,
"license": null,
"summary": "Implementation of Topsis",
"version": "1.0.3",
"project_urls": {
"Project Link": "https://github.com/anshulmahajan14/Topsis-Anshul"
},
"split_keywords": [
"topsis",
" topsis-anshul-102217060",
" anshul",
" topsis-anshul",
" 102217060"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "625d91f6921dfac01961a0f3b77972fe0f7f1930ae3402070e56eb488ede1d4d",
"md5": "42e490373ca062862235b8ae3aecbc6d",
"sha256": "17eaa30a6b0dc1219aaeda7a8bf61d2bd12c4a734317805cd951d72198148c5d"
},
"downloads": -1,
"filename": "Topsis_Anshul_102217060-1.0.3-py3-none-any.whl",
"has_sig": false,
"md5_digest": "42e490373ca062862235b8ae3aecbc6d",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 2158,
"upload_time": "2025-01-20T14:32:19",
"upload_time_iso_8601": "2025-01-20T14:32:19.889982Z",
"url": "https://files.pythonhosted.org/packages/62/5d/91f6921dfac01961a0f3b77972fe0f7f1930ae3402070e56eb488ede1d4d/Topsis_Anshul_102217060-1.0.3-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "a7af972f712252112777cf29e957d7f245992c54726ef9983fcfa34bf81b2a9a",
"md5": "af2cc3f1128237ca0601ff37680ce0de",
"sha256": "71006f2ef78af795cf1b25c15688306e5d5d1eaffa09a2915c69682a921000a3"
},
"downloads": -1,
"filename": "Topsis-Anshul-102217060-1.0.3.tar.gz",
"has_sig": false,
"md5_digest": "af2cc3f1128237ca0601ff37680ce0de",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 2310,
"upload_time": "2025-01-20T14:32:22",
"upload_time_iso_8601": "2025-01-20T14:32:22.073062Z",
"url": "https://files.pythonhosted.org/packages/a7/af/972f712252112777cf29e957d7f245992c54726ef9983fcfa34bf81b2a9a/Topsis-Anshul-102217060-1.0.3.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-01-20 14:32:22",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "anshulmahajan14",
"github_project": "Topsis-Anshul",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "topsis-anshul-102217060"
}
JSON
