TOPSIS-Nikhal-101816034 0.0.1

Python Package Implementing TOPSIS (for finding ideal and anti-ideal solution)

Topsis-Package

What is TOPSIS

TOPSIS is an acronym that stands for ‘Technique of Order Preference Similarity to the Ideal Solution’ and is a pretty straightforward MCDA method. As the name implies, the method is based on finding an ideal and an anti-ideal solution and comparing the distance of each one of the alternatives to those. It was presented in Hwang and Yoon (Multiple attribute decision making: methods and applications. Springer, Berlin, 1981) and Chen and Hwang (Fuzzy multiple attribute decision making methods. Springer, Berlin, 1992), and can be considered as one of the classical MCDA methods that has received a lot of attention from scholars and researchers. It has been successfully applied in various instances.

How to ise this Package:

TOPSIS-Nikhal-101816034 can be run by typing the following code snippet:

In Command Prompt

python topsis.py "data.csv" "1,1,1,2" "+,+,-,+" "Result.csv"

Sample Dataset

The decison-matrix should be constructed with each row representing a model alternative and each column representing criterian such as accuracy,R-Sqaure,Root Mean Squared error,Correlation etc.

Model	Corr	Rseq	RMSE	Accuracy
M1	0.79	0.62	1.25	60.89
M2	0.66	0.44	2.89	63.07
M3	0.56	0.31	1.57	62.87
M4	0.82	0.67	2.68	70.19
M5	0.75	0.56	1.3	80.39

Output

Model	Score	Rank
1	0.476957713840877	2
2	0.476572577796742	3
3	0.477495853743771	1
4	0.475616911138615	5
5	0.475948812224928	4

The Ranking are displayed in the result csv file, with 1st rank offering the best decision and last rank offering the worst decision according to the TOPSIS method.