Reimagining Sustainable Supply Chains with Quantum Intelligence
持続可能なサプライチェーンを量子インテリジェンスで再考する (AI 翻訳)
K. Bansode
🤖 gxceed AI 要約
日本語
この論文は、量子コンピューティングとAIを組み合わせた量子インテリジェンス（Quantum AI）が、サプライチェーンの持続可能性向上に寄与する可能性を論じている。生産スケジューリング、在庫管理、排出予測などの複雑な問題を解決し、ルート最適化によるコスト削減と排出削減を実現する。ハイブリッド量子古典モデルやIoT、ブロックチェーン、デジタルツインとの統合も提案している。
English
This paper discusses the potential of Quantum Intelligence (Quantum AI)—a combination of quantum computing and artificial intelligence—to enhance supply chain sustainability. It addresses complex problems like production scheduling, inventory management, and emissions forecasting, enabling route optimization, cost reduction, and lower carbon emissions. It also proposes hybrid quantum-classical models and integration with IoT, blockchain, and digital twins.
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
日本はサプライチェーン全体の脱炭素化と量子コンピューティング（Q-LEAPなど）への投資を進めており、本論文は両領域の融合を示す概念的な展望を提供する。しかし、具体的な実装や日本企業向けの事例は含まれていない。
In the global GX context
Globally, supply chain decarbonization is a growing focus, and Quantum AI offers a futuristic approach. The paper is conceptual and lacks empirical validation, so its contribution to current disclosure or transition finance frameworks is limited.
👥 読者別の含意
🔬研究者:Provides a high-level overview of Quantum AI concepts for sustainable supply chain optimization.
🏢実務担当者:May inspire long-term R&D strategies for logistics and supply chain sustainability.
📄 Abstract（原文）
Sustainable supply chains are becoming increasingly important as businesses strive to reduce environmental impact while maintaining efficiency and profitability. One emerging solution is Quantum Intelligence (Quantum AI)—a powerful combination of quantum computing and artificial intelligence that can handle highly complex and data-intensive supply chain problems. Quantum AI leverages unique quantum principles such as superposition and entanglement to explore a vast number of possible solutions simultaneously. This enables better decision-making in areas like production scheduling, inventory management, and emissions forecasting. As a result, organizations can optimize delivery routes, reduce operational costs, and significantly lower carbon emissions, contributing to more sustainable and environmentally responsible supply chains. A key approach in this field is the hybrid quantum-classical model, which combines the data-processing strengths of classical computing with the advanced computational capabilities of quantum systems. This hybrid approach helps overcome current limitations in quantum hardware, such as noise, limited qubits, and high error rates, making Quantum AI more practical for real-world applications. In addition, integrating technologies like the Internet of Things (IoT), blockchain, and digital twins further enhances supply chain performance. IoT devices provide real-time data from sensors, blockchain ensures transparency and traceability, and digital twins allow simulation of supply chain operations to predict environmental impacts and test different scenarios. Overall, Quantum AI represents a promising step toward building smarter, more efficient, and sustainable supply chains that can adapt to modern challenges while supporting global environmental goals.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.22214/ijraset.2026.79072first seen 2026-06-23 06:19:09
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
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。