| Name | Topsis-Samarjot-102003242 JSON |
| Version |
1.0
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| Summary | Python package implementing TOPSIS multi-criteria decision making method. |
| upload_time | 2023-01-25 10:37:16 |
| maintainer | |
| docs_url | None |
| author | Samarjot Singh |
| requires_python | |
| license | MIT |
| keywords |
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# TOPSIS multi-criteria decision making - Python
**Assignment 1 : UCS654**
Submitted By: **Samarjot Singh 102003242**
***
## What is TOPSIS?
**TOPSIS**, known as Technique for Order of Preference by Similarity to Ideal Solution, is a multi-criteria decision analysis method. It compares a set of alternatives based on a pre-specified criterion. The method is used in the business across various industries, every time we need to make an analytical decision based on collected data. More details at [YouTube](https://www.youtube.com/watch?v=kfcN7MuYVeI&ab_channel=ManojMathew).
<br>
## How to run this package:
TOPSIS-Samar 102003242 can be used by running following command in CMD:
```
>> topsis 102003242-data.csv "1,1,1,2,1" "-,+,+,-,+" 102003242-result.csv
```
<br>
## Sample dataset
The decision matrix should be constructed with each row representing a Fund Name, and each column representing a criterion P1, P2, P3, P4, P5.
Fund Name | P1 | P2 | P3 | P4 | P5
------------ | ------------- | ------------ | ------------- | ------------- | ------------
M1 | 0.72 | 0.52 | 4.4 | 62.1 | 16.94
M3 | 0.72 | 0.52 | 5.7 | 48.6 | 13.91
M2 | 0.76 | 0.58 | 4.2 | 39.4 | 11.21
M4 | 0.68 | 0.46 | 6.7 | 50 | 14.46
M5 | 0.67 | 0.45 | 5.2 | 62.2 | 17.13
M6 | 0.86 | 0.74 | 5.2 | 63.8 | 17.65
M7 | 0.93 | 0.86 | 4.5 | 65.6 | 17.97
M8 | 0.78 | 0.61 | 5.4 | 69.7 | 19.12
Weights(`w`) and Impacts(`i`) will be applied later in the code.
<br>
## Output
```
Row No. Performance Score Rank
-------- ------------------- ------
3 0.332629 8
2 0.555383 1
1 0.548848 2
4 0.530816 3
5 0.354290 6
6 0.421567 5
7 0.435080 4
8 0.353907 7
```
<br>
The rankings are displayed in the form of a table with the 1st rank offering us the best decision and last rank offering the worst decision making, according to TOPSIS method.
Raw data
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"description": "# TOPSIS multi-criteria decision making - Python\r\n\r\n**Assignment 1 : UCS654**\r\n\r\nSubmitted By: **Samarjot Singh 102003242**\r\n\r\n***\r\n\r\n## What is TOPSIS?\r\n\r\n**TOPSIS**, known as Technique for Order of Preference by Similarity to Ideal Solution, is a multi-criteria decision analysis method. It compares a set of alternatives based on a pre-specified criterion. The method is used in the business across various industries, every time we need to make an analytical decision based on collected data. More details at [YouTube](https://www.youtube.com/watch?v=kfcN7MuYVeI&ab_channel=ManojMathew).\r\n\r\n<br>\r\n\r\n## How to run this package:\r\n\r\nTOPSIS-Samar 102003242 can be used by running following command in CMD:\r\n\r\n```\r\n>> topsis 102003242-data.csv \"1,1,1,2,1\" \"-,+,+,-,+\" 102003242-result.csv\r\n```\r\n\r\n<br>\r\n\r\n## Sample dataset\r\n\r\nThe decision matrix should be constructed with each row representing a Fund Name, and each column representing a criterion P1, P2, P3, P4, P5.\r\n\r\nFund Name | P1 | P2 | P3 | P4 | P5\r\n------------ | ------------- | ------------ | ------------- | ------------- | ------------\r\nM1 |\t0.72 | 0.52\t| 4.4 | 62.1 | 16.94\r\nM3 |\t0.72 | 0.52\t| 5.7 | 48.6 | 13.91\r\nM2 |\t0.76 | 0.58\t| 4.2 | 39.4 | 11.21\r\nM4 |\t0.68 | 0.46\t| 6.7 | 50 | 14.46\r\nM5 |\t0.67 | 0.45\t| 5.2 | 62.2 | 17.13\r\nM6 |\t0.86 | 0.74\t| 5.2 | 63.8 | 17.65\r\nM7 |\t0.93 | 0.86\t| 4.5 | 65.6 | 17.97\r\nM8 |\t0.78 | 0.61\t| 5.4 | 69.7 | 19.12\r\n\r\nWeights(`w`) and Impacts(`i`) will be applied later in the code.\r\n\r\n<br>\r\n\r\n## Output\r\n\r\n```\r\n Row No. Performance Score Rank\r\n-------- ------------------- ------\r\n 3 0.332629 8\r\n 2 0.555383 1\r\n 1 0.548848 2\r\n 4 0.530816 3\r\n 5 0.354290 6\r\n 6 0.421567 5\r\n 7 0.435080 4\r\n 8 0.353907 7\r\n```\r\n<br>\r\nThe rankings are displayed in the form of a table with the 1st rank offering us the best decision and last rank offering the worst decision making, according to TOPSIS method.\r\n",
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