Bibliographic Details
| Title: |
IMPLEMENTATION OF AN ENHANCED CRITERION WEIGHTING METHOD BASED ON STANDARD DEVIATION IN MULTI-CRITERIA DECISION-MAKING. |
| Authors: |
Mai, Nguyen Trong1 nguyentrongmai@haui.edu.vn |
| Source: |
EUREKA: Physics & Engineering. 2026, Issue 2, p129-139. 11p. |
| Subject Terms: |
*Multiple criteria decision making, *Standard deviations, *Decision making |
| Abstract: |
MCDM (Multi-Criteria Decision-Making) involves evaluating and ranking alternatives based on multiple criteria to select optimal choices. The weights of criteria are critical parameters directly influencing MCDM outcomes. A weighting method is considered effective if it maintains the stability of alternative rankings across various techniques. This research proposes a novel hybrid approach for calculating criterion weights that incorporates the standard deviation of criteria. The research integrates the objective LOPCOW (LOgarithmic Percentage Change-driven Objective Weighting) method, which utilizes data dispersion to establish initial relative importance, with the subjective ROC (Rank Order Centroid) method to compute final weights. This hybrid framework leverages the objective strengths of LOPCOW in capturing intrinsic information and the subjective efficiency of ROC in determining the "centroid of potential weights". Qualitatively, the method overcomes the bias of purely subjective methods and the potential preference misalignment of purely objective ones. Quantitatively, the efficacy was assessed through three case studies involving benefit, cost, and mixed criteria. The results consistently demonstrated superior rank stability compared to the standalone LOPCOW method. Specifically, the average Spearman’s correlation coefficient increased from 0.9619 to 0.9905 in Example 1, from 0.9204 to 0.9481 in Example 2, and significantly from 0.7900 to 0.9400 in a real-world injection molding machine selection problem. These numerical gains prove the method’s ability to minimize rank consistency conflicts across different MCDM techniques. This approach serves as a highly effective and reliable tool for engineers and managers to optimize resources and reduce risks in technical investment decisions. [ABSTRACT FROM AUTHOR] |
| Database: |
Academic Search Index |