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インターバル値のファームで持続可能な物流管理のための新しい意思決定支援システム

Umar Ali^1,2, Junxiang Li^1,2, Qin Qi³

¹Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China.

Scientific reports

|August 29, 2025

まとめ

この研究では,インターバル値のフェルメタン画像模糊セット (IVFPFS) を使用した持続可能な物流管理のための新しい意思決定方法が紹介されています. このアプローチは,レジリエンスを高め,複雑な物流上の課題に現実的な解決策を提供します.

科学分野:

ぼんやりとした集合論
運用研究
持続可能な物流管理

背景:

持続可能な物流管理には複雑で不安定な意思決定プロセスが必要です
既存の方法は物流に固有の不確実で信頼性の低いデータと戦っています.
インターバル値のフェルメタン画像模糊セット (IVFPFS) は,このようなデータを扱うための堅牢な枠組みを提供します.

研究の目的:

持続可能な物流管理のための新しいマルチ属性意思決定 (MADM) の方法論を開発する.
インターバル値のフェルメタン画像の fuzzy アインシュタイン加重平均 (IVFPFEWA) と幾何学 (IVFPFEWG) オペレーターを導入および分析する.
持続可能な物流の意思決定の正確性と現実性を高める

主な方法:

不確実なデータをモデル化するために,インターバル値のフェルメア画像のぼやけたセット (IVFPFS) を使用する.
IVFPFEWAとIVFPFEWGの集積オペレーターを開発し,適用する.
IVFPFS構造内のアインシュタイン集積に基づいた新しいMADM方法の実装.
比較分析と感度分析を行い,提案された方法を検証する.

主要な成果:

提案されたMADMの方法論は,物流における複雑で不確実なデータを効果的に処理します.
IVFPFEWAとIVFPFEWGの事業者は,IVFPFSの枠組み内で集積の熟練性を証明しています.
比較分析と感度分析により,戦略の一貫性,有効性,実用性が確認された.
開発された技術は,レジリエントな物流システムの管理のための現実的な決定を提供します.

結論:

IVFPFSとアインシュタインオペレータを使用した新しいMADMアプローチは,持続可能な物流の意思決定に優れたソリューションを提供します.
この方法は,従来の物流の複雑さを管理する戦略よりも現実的で機能的です.
この研究は,物流システムのレジリエンスと持続可能性を高めるための貴重なツールとなる.

キーワード:

意思決定アインシュタイン集積演算子インターバル値のフェルメタン画像のぼやけセットロジスティック管理システム MADM について

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