Multi-criteria decision making problems are well-known problems. This paper mainly investigates a particular type of multi-criteria aggregation imperative called prioritized aggregation. We first introduce the concepts of measure, additive measure and Choquet integral. Then, we propose a prioritized measure-guided aggregation operator based on the ordered weighted averaging (OWA) operator and Choquet integral. We develop the maximin disparity method to get the quantity of each priority hierarchy in the prioritized measure. Besides, we introduce the decision maker's benchmark into the prioritized measure. Finally, we illustrate the effectiveness of the proposed prioritized aggregation operator through two numerical examples and compare them with previous operators.
This paper mainly investigates a special kind of multicriteria decision-making problem, in which all the criteria can be divided into several hierarchies and the criteria in the higher hierarchy have priorities over those in the lower hierarchy. It implies that the loss of the higher priority criterion can't be compensated by the gain of the lower prioritized criteria. As we know, fuzzy measures can well represent the interactions between criteria. In this situation, we develop a new fuzzy measure called weakly ordered prioritized measure (WOPM) to express the priority rule among the weakly ordered prioritized criteria. On the basis of the WOPM, we use discrete Choquet integral to construct a new WOPM-guided aggregation (WOPMGA) operator. To understand the priority property of this aggregation operator deeply, we get all the criteria's Shapley values and make an analysis of all criteria's Shapley values with different parameter values. Through analysis, we can find that the WOPMGA operator has the properties of boundedness, idempotency and monotonicity. Finally, we give several practical examples to illustrate the effectiveness of this aggregation operator. C 2014 Wiley Periodicals, Inc.
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