AW: An Aggregated Weighting Method for Balancing Expert Opinions

Bui Vinh Binh; Nguyen Hong Son; Dang Xuan Thao; Vo Thi Nhu Uyen; Dang Tien Hieu

doi:10.48084/etasr.18464

Authors

Bui Vinh Binh Hanoi University of Industry, Hanoi, Vietnam
Nguyen Hong Son Hanoi University of Industry, Hanoi, Vietnam
Dang Xuan Thao Hanoi University of Industry, Hanoi, Vietnam
Vo Thi Nhu Uyen Hanoi University of Industry, Hanoi, Vietnam
Dang Tien Hieu Hanoi University of Industry, Hanoi, Vietnam

Volume: 16 | Issue: 3 | Pages: 35154-35161 | June 2026 | https://doi.org/10.48084/etasr.18464

Received: 1 March 2026 | Revised: 23 March 2026 and 27 March 2026 | Accepted: 29 March 2026 | Online: 8 April 2026

Corresponding author: Nguyen Hong Son

Abstract

Determining criteria weights is significant in multi-objective optimization, particularly in Multi-Criteria Decision-Making (MCDM) problems. This study introduces a novel criteria weighting approach, the Aggregated Weighting (AW) method, which integrates three widely used subjective weighting techniques: Rank Reciprocal (RR), Rank Sum (RS), and Rank Order Centroid (ROC). Its effectiveness is demonstrated through three case studies, including two synthetic examples and one real-world application involving the evaluation of wood milling machines. The results show that the AW method consistently produces rankings that reflect a balanced consensus compared to those obtained using the individual component methods (RR, RS, and ROC). Therefore, the AW method offers a practical and reliable framework for supporting group decision-making when different preferences exist regarding the choice of weighting technique.

Keywords:

AW method, weight method, MCDM

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