From the figures, it is possible to observe the differences between the two methodologies. Although both methods are based on distances from ideal solutions, the concept of TOPSIS suggests that the most preferred alternative should not only have the shortest distance from the ideal solution, but also be farthest from the anti-ideal solution.
But compromise programming defines an ideal solution and then tries to minimize the distances among this ideal point and the set of decision alternatives.
For instance, let us compare Canon 1000D and Nikon D3000 for the student.
In TOPSIS, the distance from the ideal solution of Canon 1000D is 0.032, and 0.034
for Nikon D3000, whereas the distance from the anti-ideal solution of Canon 1000D is 0.083, and 0.075 for Nikon D3000. In this case,Canon 1000D is found as preferable because of the higher distance from the anti-ideal solution.
However, in compromise programming Nikon D3000 is preferable since compromise programming tries to minimize only the distance from the ideal solution.
We can conclude that for the users who both care to be close to the ideal solution and far from the anti-ideal solution, TOPSIS is preferable.
Our interviewers were generally focused on how good an alternative is in a given criterion and sub-criterion by ignoring how bad the alternative is.
Therefore, choosing the compromise programming to rank the alternatives was more suitable than TOPSIS
in our case.