A Novel Objective Composite Weighting and Gain-Oriented Ranking Approach (OFGORCUN) for Multi-Criteria Decision Making
DOI:
https://doi.org/10.65069/jessd21202613Keywords:
OFGORCUN, Multi-Criteria Decision Making , MCDM, Objective weighting, Gain-Oriented ranking, Composite weighting, Logistics service provider selection, Last mile delivery company evaluation, Decision analysisAbstract
This study proposes the OFGORCUN (Optimized Factor-based Gain-Oriented Ranking with Composite Utility and Normalization) approach, which is a new method that deals with weighting and ranking processes in multi-criteria decision-making a new method for weighting and ranking in multi-criteria decision-making (MCDM) problems that integrates and makes fully objective the weighting and ranking processes (MCDM) problems in an integrated and completely objective structure. The proposed method offers a more balanced, data-driven weighting mechanism compared to existing approaches in the literature by combining entropy-based information measures, distributional structure as expressed by standard deviation, and dissociation power based on correlations between criteria into a single composite formula to determine criterion weights. In the ranking phase of the method, the final performance scores of the alternatives are obtained using a normalized gain-based benefit function that combines the benefit and cost criteria. To demonstrate the feasibility and performance of the proposed model, the problem of selecting a cargo company was used as a case study, and different logistics service providers were evaluated against multiple operational, cost, and capacity criteria. The findings show that C4 – Total number of distributors is the most decisive and dominant criterion, while the most suitable carrier alternative is A8 DHL. In this context, it shows that the OFGORCUN method has strong decomposition capabilities for high-variance, multidimensional datasets and clearly reveals performance differences between large-scale logistics companies and local companies. In addition, the sequencing results obtained with the method were compared with common MSDV methods such as TOPSIS, MARCOS, and CRADIS, and the method's sensitivity to changes was evaluated using a Monte Carlo simulation. In addition, the effects of changes in criterion weights on the final results were evaluated. Based on the results, the proposed approach produced more consistent and distinctive results. In conclusion, the OFGORCUN method makes a unique contribution to the MCDM literature thanks to its completely objective structure, its lack of parameters, and its integration of multiple information criteria. It is considered a model that can be effectively used as a decision-support tool in logistics, supply chain management, and related fields.
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