Comparison of MCDA methods based on distance to reference objects : a simple study case

With technology development approach to cleaning changed as well. The vacuum cleaner robot market suggests a wide choice of different models. Choosing the model with optimal price, engine power, noise level, and other significant parameters is troublesome. In this case, MCDA methods can be helpful, which also proofs that it can also be used to daily decision problems.

In this paper, two of them are used: the COMET and the TOPSIS. The first step is to analyze the subject and determine characteristic criteria. The second – selecting some market models which would be ranked. The third – normalize data for the TOPSIS method. After these preparations, both methods can be applied to our models, and alternatives can be ranked. Two MCDA methods were selected to compare MCDA methods based on the distance to reference objects. This simple study case also shows that the COMET method returns more accurate results and presents the advantages of this method. In conclusion, further research directions are shortly discussed.