Modeling Dual-Uncertainty In Sustainable Supplier Selection Using Bipolar Complex Pythagorean Fuzzy Sets
バイポーラ複合ピタゴラスファジー集合を用いた持続可能なサプライヤー選定における二重不確実性のモデリング (AI 翻訳)
M. Arar, Hariwan Z. Ibrahim
🤖 gxceed AI 要約
日本語
本研究は、持続可能なサプライヤー選定において、経済・環境・社会の相反する基準と不確実性を扱うため、バイポーラ複合ピタゴラスファジー集合（BCPFS）に基づく意思決定フレームワークを提案する。グリーンサプライチェーンの事例研究では、コスト重視から完全にバランスの取れた持続可能性重視までの6つのサプライヤー戦略を評価し、バランス型が最適であることを示した。従来のファジー手法と比較して、提案手法はよりリッチで安定した解を提供する。
English
This study proposes a decision-making framework based on bipolar complex Pythagorean fuzzy sets (BCPFSs) to handle conflicting criteria, uncertainty, and dual evaluations in sustainable supplier selection. A case study on green supply chain management evaluates six supplier strategies, finding the balanced sustainability approach optimal. The new aggregation operators provide richer and more stable rankings than conventional fuzzy methods.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本のサプライチェーンにおける環境配慮型調達の強化が求められる中、本手法は企業がサプライヤー選定においてカーボン排出や廃棄物管理などのGX要素を定量的に評価するツールとして活用できる。
In the global GX context
As global supply chains face increasing pressure to decarbonize, this fuzzy decision-making framework offers a practical tool for integrating sustainability criteria—including carbon emissions and waste—into supplier selection, supporting green supply chain management (GSCM) initiatives worldwide.
👥 読者別の含意
🔬研究者:Provides a new methodological extension of fuzzy sets for multi-criteria decision-making in sustainability contexts.
🏢実務担当者:Offers a structured approach for evaluating supplier sustainability performance amid uncertainty.
📄 Abstract（原文）
Managing sustainability in modern supply chains requires decision-making tools that can accommodate conflicting criteria, uncertain data, and evaluations that involve both positive and negative impacts. To address these challenges, this study develops a new decision-making framework based on bipolar complex Pythagorean fuzzy sets (BCPFSs). The model integrates bipolarity, complex-valued membership degrees, and Pythagorean structures to capture the nuanced interplay of economic, environmental, and social considerations. On this foundation, two aggregation operators—the bipolar complex Pythagorean fuzzy weighted averaging (BCPFWA) and weighted geometric (BCPFWG) operators—are introduced to synthesize multidimensional information while preserving uncertainty and dual evaluations. The applicability of the framework is demonstrated through a case study on green supply chain management (GSCM). Six supplier strategies, ranging from cost-oriented to fully balanced sustainability-focused approaches, are assessed against eight attributes including cost efficiency, product quality, carbon emissions, waste management, technological integration, and social responsibility. The analysis reveals that the balanced sustainability supplier emerges as the most effective choice, consistently ranked highest by both operators. Comparative results with conventional fuzzy aggregation approaches show that the proposed operators provide richer, more stable, and more interpretable rankings, especially when trade-offs between cost and sustainability are present. This research contributes to both theory and practice: it extends the scope of fuzzy decision-making by unifying multiple existing models as special cases, and it offers a practical toolset for organizations seeking resilient and environmentally responsible supply chain solutions. The findings demonstrate that BCPF-based aggregation can enhance strategic decision-making in contexts where sustainability and uncertainty are inseparably linked.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.28924/2291-8639-24-2026-17first seen 2026-05-05 22:21:36
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。