Weighted normalized fuzzy decision matrix.

Rice, being a staple food in many countries, necessitates the identification of reliable suppliers to ensure a steady supply. Consequently, it is vital to establish trustworthy vendors for various types of this essential grain who can meet stringent product quality standards. This study aims to identify, analyze, rank, and select primary rice suppliers. The study emphasizes the importance of selecting and managing suitable providers to meet customer demands, proposes a ranking model for rice suppliers, and introduces developed fuzzy MCDM techniques. It proposes an integrated model for selecting rice suppliers, considering factors related to the processes before, during, and after selecting providers within a defined framework. The outcomes shows that rice supplier selection strategy can efficiently identify reliable rice suppliers, improve buyer value, reduce procurement risk, enhance efficiency, and establish strong supply chain relationships in complex decision-making processes. To assess suppliers, the study introduces two advanced integrated approaches and compares them. The fuzzy entropy weight method (EWM) was used to determine the criteria weights. The ranking of rice suppliers was achieved using a fuzzy multi-objective optimization based on ratio analysis (MOORA), fuzzy complex proportional assessment (COPRAS), and combinations of these two methods in different approaches. The methodology supports decision-makers in a rapidly evolving global environment by assisting importers, traders, suppliers, procurement, and logistics management, particularly for non-rice-cultivating countries in rice importation and supplier selection. The numerical analysis is grounded in a real-world case study of selecting rice suppliers in Jordan. The findings reveal that the various strategies yield both similar and different results. Furthermore, the integrated method is considered the most accurate for evaluating rice imports and suppliers, aligning closely with the reality of the current situation.

水稻作为诸多国家的主食，亟需甄选可靠供应商以保障稳定供给。因此，针对这类核心粮食品类的各类别，遴选能够满足严苛产品质量标准的可信供应商至关重要。本研究旨在识别、分析、排序并甄选核心水稻供应商。
本研究强调遴选与管理适配供应商以满足客户需求的重要性，提出了水稻供应商排序模型，并介绍了改进的模糊多准则决策（Fuzzy MCDM）技术。本研究提出了一套集成化的水稻供应商遴选模型，在既定框架内纳入供应商遴选前、遴选中与遴选后各环节相关的考量因素。
研究结果表明，在复杂决策流程中，水稻供应商遴选策略可有效甄别可靠供应商，提升采购方价值，降低采购风险，提升运营效率，并构建稳固的供应链合作关系。
为开展供应商评估，本研究引入两种先进集成评估方法并进行对比分析。研究采用模糊熵权法（Fuzzy Entropy Weight Method, EWM）确定各准则权重。本研究基于模糊比率分析多目标优化法（Fuzzy Multi-Objective Optimization Based on Ratio Analysis, MOORA）、模糊复杂比例评估法（Fuzzy Complex Proportional Assessment, COPRAS）以及两种方法的多种组合方式，实现水稻供应商的排序。
该方法论可为快速变化的全球环境中的决策者提供支持，助力进口商、贸易商、供应商、采购与物流管理人员开展工作，尤其适用于非水稻种植国家的水稻进口与供应商遴选场景。数值分析基于约旦开展的水稻供应商遴选真实案例展开。
研究结果显示，不同策略的评估结果既有相似之处，也存在差异。此外，集成化方法被认为是评估水稻进口与供应商的最精准方法，与当前实际情况高度契合。