Decision Making in the Assignment Process by Using the Hungarian Algorithm With Owa Operators

Abstract

Assignment processes permit to coordinate two set of variables so each variable of the first set is connected to another variable of the second set. This paper develops a new assignment algorithm by using a wide range of aggregation operators in the Hungarian algorithm. A new process based on the use of the ordered weighted averaging distance (OWAD) operator and the induced OWAD (IOWAD) operator in the Hungarian algorithm is introduced. We refer to it as the Hungarian algorithm with the OWAD operator (HAOWAD) and the Hungarian algorithm with the IOWAD operator (HAIOWAD). The main advantage of this approach is that we can provide a parameterized family of aggregation operators between the minimum and the maximum. Thus, the information can be represented in a more complete way. Furthermore, we also present a general framework by using generalized and quasi-arithmetic means. Therefore, we can consider a wide range of particular cases including the Euclidean and the Minkowski distance. The paper ends with a practical application of the new approach in a financial decision making problem regarding the assignment of investments.

Fuzzy Branch-and-Bound Algorithm with OWA Operators in the Case of Consumer Decision Making

“…In this article, we use the OWA operator in the normalized process from the Hamming distance. In addition, we use the OWAD operator in the assignment process [55,56]. It is very easy to apply since we can consider our opinion when forming the similarity relationships, but at the same time, we can underestimate or overestimate this position and see if the results achieved are the same or different when developing the assignment process.…”

“…The focus is on assignment decision-making problems based on the Branch-and-bound algorithm. Note that in the literature, there are many other methods [8,56,58].…”

Government transparency measurement through prioritized distance operators

“…Also, many applications in decision making problems and multiple attribute decision making has also been developed [32,48], 2) the Probabilistic OWA (POWA) operator [30], that some extension using interval numbers [50] and linguistic variables [28]. In addition, some applications in finance and fuzzy environment have been developed [35,52], 3) the Induced OWA (IOWA) operator [38], that has developed extensions using moving average, heavy weights and intuitionistic fuzzy sets [6,51] and some applications in multiple criteria decision making, safety programs and cluster analysis have been done [5,11,56] and 4) the Hamming distance operator [45] that has been applied in many areas such as sports and finance [8,19]. A generalization of the PIPOWAD operator is presented by using quasi-arithmetic means [21,23].…”

Expertons and uncertain averaging operators versus correlational approaches

“…Other operators based on interval numbers are the uncertain average (UA), the uncertain weighted average (UWA) and the uncertain probabilistic aggregation (UPA). Several studies use this kind of aggregation operators, such as the interval gray linguistic variables (Jin and Liu, 2010), the linguistic aggregation operators such as the linguistic probabilistic weighted average (Merigó et al, 2016), decision-making under risk, interval vague set and the TOPSIS method (Liu, 2009(Liu, , 2010Zeng and Xiao, 2016), the induced and uncertain heavy OWA operators (Merigó and Casanovas, 2011), the Hungarian algorithm with the induced ordered weighted averaging distance (HAIOWAD) (Vizuete-Luciano et al, 2015), the uncertain linguistic hybrid geometric mean operator (Wei, 2009) or the uncertain induced Minkowski ordered weighted average distance operator (Zeng, 2013). Merigó (2011b) proposed a new decision-making approach based on an operator that is the result of the union between the UWA and the UPA operators.…”