Metadata-Version: 2.1
Name: Topsis-Manish-101903228
Version: 0.0.2
Summary: A package Calculates Topsis Score and Rank them accordingly, for example selection of best project
Home-page: UNKNOWN
Author: Manish Sharma
Author-email: manish1206s@gmail.com
License: MIT
Description: ## Topsis-Manish-101903228
        
        # TOPSIS
        
        Submitted By: **Manish Sharma - 101903228**.
        
        Type: **Package**.
        
        Title: **TOPSIS method for multiple-criteria decision making (MCDM)**.
        
        Version: **0.0.2**.
        
        Date: **26-Feb-2022**.
        
        Author: **Manish Sharma**.
        
        Contact: **<manish1206s@gmail.com>**.
        
        Submitted To :**Dr. Prashant Singh Rana**
        
        Description: **Evaluation of alternatives based on multiple criteria using TOPSIS method.**.
        
        ---
        
        ## What is TOPSIS?
        
        **T**echnique for **O**rder **P**reference by **S**imilarity to **I**deal **S**olution
        (TOPSIS) originated in the 1980s as a multi-criteria decision making method.
        TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution,
        and greatest distance from the negative-ideal solution.
        
        <br>
        
        ## How to install this package:
        
        ```
        >> pip install Topsis-Manish-101903228
        ```
        
        ### In Command Prompt Run with the following parameters
        
        ```
        >> topsis input_data_file.csv "1,1,1,1,1" "+,-,+,-,+" result.csv
        ```
        
        ## Input file (input_data_file.csv)
        
        The decision matrix should be constructed with each row representing a Model alternative, and each column representing a criterion.
        
        | Model | p1          | p2            | p3   |p4        |
        | ----- | ----------- | ------------- | ---- | -------- |
        | M1    | 0.11        | 0.2           | 1.85 | 70.89    |
        | M2    | 0.68        | 0.454         | 2.89 | 73.07    |
        | M3    | 0.56        | 0.31          | 1.57 | 2.87     |
        
        
        
        Weights (`weights`) is not already normalised will be normalised later in the code.
        
        Information of benefit positive(+) or negative(-) impact criteria should be provided in `impacts`.
        
        <br>
        
        ## Output file (result.csv)
        
        
        | Model | p1          | p2            | p3   |p4        | Topsis_score | Rank |
        | ----- | ----------- | ------------- | ---- | -------- | ------------ | ---- |
        | M1    | 0.11        | 0.2           | 1.85 | 70.89    | 0.5722       | 3    |
        | M2    | 0.68        | 0.454         | 2.89 | 73.07    | 0.7722       | 2    |
        | M3    | 0.56        | 0.31          | 1.57 | 2.87     | 0.7872       | 1    |
        
        <br>
        The output file contains columns of input file along with two additional columns having (Topsis score) and (Rank)
Platform: UNKNOWN
Description-Content-Type: text/markdown
