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Decision-making problems in an uncertain environment can be solved using fuzzy multi-criteria decision-making methods. One such problem is the problem of housing selection, where it is challenging to determine data explicitly. Many people struggle with the difficulty of determining what conditions they would like to live in. It is hard for them to determine their housing preferences based only on data from the offers. Numerical values do not clearly define many parameters. Both apartment buyers and realtors use values such as much or little, precisely represented by fuzzy numbers. This paper proposes a solution to the housing selection problem using fuzzy MCDA techniques such as Fuzzy MMOORA, Fuzzy WASPAS, Fuzzy TOPSIS and Fuzzy VIKOR. Then the obtained ranking of alternatives was compared using ranking similarity coefficients such as weighted Spearman coefficient and WS ranking similarity coefficient. The proposed approaches produce similar results, indicating that the decision models reflect preferences well. At the end of the paper, conclusions and further research directions are presented.
Kizielewicz et al. (Fri,) studied this question.