A Python package for handling problems of Multiple Criteria Decision Making(MCDM) for a given dataset.
Project description
Topsis-Nipun-102003674
Topsis-Nipun-102003674 is a Python package for dealing with Multiple Criteria Decision Making(MCDM) problems by using Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS). Topsis is a method of compensatory aggregation that compares a set of alternatives, 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.
Installation
Use the package manager pip to install Topsis-Nipun-102003674
Syntax
topsis <InputDataFile> <Weights> <Impacts> <ResultFileName>
Example:
topsis inputfile.csv 1,2,1,2,1 +,+,-,+,- result.csv
Example
Sample Input Data
Name | P1 | P2 | P3 | P4 | P5 |
---|---|---|---|---|---|
M1 | 0.71 | 0.5 | 3.8 | 40.8 | 11.5 |
M2 | 0.94 | 0.88 | 5.3 | 56.2 | 15.83 |
M3 | 0.85 | 0.72 | 4 | 30.5 | 9.02 |
M4 | 0.61 | 0.37 | 5.4 | 56.9 | 15.82 |
M5 | 0.91 | 0.83 | 3.4 | 53.4 | 14.64 |
Weights: 1,1,1,1,1 Impacts: +,+,+,+,+
Sample Output Data
Name | P1 | P2 | P3 | P4 | P5 | Score | Rank |
---|---|---|---|---|---|---|---|
M1 | 0.71 | 0.5 | 3.8 | 40.8 | 11.5 | 0.3015751942839768 | 5 |
M2 | 0.94 | 0.88 | 5.3 | 56.2 | 15.83 | 0.97815026808521971 | 1 |
M3 | 0.85 | 0.72 | 4 | 30.5 | 9.02 | 0.4172925776259159 | 4 |
M4 | 0.61 | 0.37 | 5.4 | 56.9 | 15.82 | 0.5053936295885693 | 3 |
M5 | 0.91 | 0.83 | 3.4 | 53.4 | 14.64 | 0.6774035368116197 | 2 |
Note
- Enter the path of your input csv file.
- Enter the weights and impacts vector with each entry separated by commas.
- Enter the name of output file in .csv format.
- The Output file will be created in the current working directory
License
© 2023 Nipun Garg This repository is licensed under the MIT license. See LICENCE for details.
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