Abstract
An
m
-polar fuzzy set is a powerful mathematical model to analyze multipolar, multiattribute, and multi-index data. The
m
-polar fuzzy sets have appeared as a useful tool to portray uncertainty in multiattribute decision making. The purpose of this article is to analyze the aggregation operators under the
m
-polar fuzzy environment with the help of Dombi norm operations. In this article, we develop some averaging and geometric aggregation operators using Dombi
t
-norm and
t
-conorm to handle uncertainty in
m
-polar fuzzy (
m
F
, henceforth) information, which are
m
F
Dombi weighted averaging (
m
FDWA
) operator,
m
F
Dombi ordered weighted averaging (
m
FDOWA
) operator,
m
F
Dombi hybrid averaging (
m
FDHA
) operator,
m
F
Dombi weighted geometric (
m
FDWG
) operator,
m
F
Dombi weighted ordered geometric operator, and
m
F
Dombi hybrid geometric (
m
FDHG
) operator. We investigate properties, namely, idempotency, monotonicity, and boundedness, for the proposed operators. Moreover, we give an algorithm to solve multicriteria decision-making issues which involve
m
F
information with
m
FDWA
and
m
FDWG
operators. To prove the validity and feasibility of the proposed model, we solve two numerical examples with our proposed models and give comparison with
m
F
-ELECTRE-I approach (Akram et al. 2019) and
m
F
Hamacher aggregation operators (Waseem et al. 2019). Finally, we check the effectiveness of the developed operators by a validity test.